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ORCIDRichard G. Baraniuk
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- affiliation: Rice University, Houston, TX, USA
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2020 – today
- 2024
[j123]Vishwanath Saragadam
, Randall Balestriero, Ashok Veeraraghavan, Richard G. Baraniuk:
DeepTensor: Low-Rank Tensor Decomposition With Deep Network Priors. IEEE Trans. Pattern Anal. Mach. Intell. 46(12): 10337-10348 (2024)- [j122]Daniel LeJeune, Pratik Patil, Hamid Javadi, Richard G. Baraniuk, Ryan J. Tibshirani:
Asymptotics of the Sketched Pseudoinverse. SIAM J. Math. Data Sci. 6(1): 199-225 (2024) - [j121]Yehuda Dar, Daniel LeJeune, Richard G. Baraniuk:
The Common Intuition to Transfer Learning Can Win or Lose: Case Studies for Linear Regression. SIAM J. Math. Data Sci. 6(2): 454-480 (2024) - [j120]Lorenzo Luzi, Paul M. Mayer, Josue Casco-Rodriguez, Ali Siahkoohi, Richard G. Baraniuk:
Boomerang: Local sampling on image manifolds using diffusion models. Trans. Mach. Learn. Res. 2024 (2024) - [j119]Hossein Babaei, Sina Alemohammad, Richard G. Baraniuk:
Covariate Balancing Methods for Randomized Controlled Trials Are Not Adversarially Robust. IEEE Trans. Neural Networks Learn. Syst. 35(4): 5014-5026 (2024) - [c261]Shashank Sonkar, Kangqi Ni, Lesa Tran Lu, Kristi Kincaid, John S. Hutchinson, Richard G. Baraniuk:
Automated Long Answer Grading with RiceChem Dataset. AIED (1) 2024: 163-176 - [c260]Shashank Sonkar, Naiming Liu, Debshila Basu Mallick, Richard G. Baraniuk:
Marking: Visual Grading with Highlighting Errors and Annotating Missing Bits. AIED (1) 2024: 309-323 - [c259]Shashank Sonkar, Kangqi Ni, Sapana Chaudhary, Richard G. Baraniuk:
Pedagogical Alignment of Large Language Models. EMNLP (Findings) 2024: 13641-13650 - [c258]Shashank Sonkar, Naiming Liu, Richard G. Baraniuk:
Student Data Paradox and Curious Case of Single Student-Tutor Model: Regressive Side Effects of Training LLMs for Personalized Learning. EMNLP (Findings) 2024: 15543-15553 - [c257]Shashank Sonkar, Naiming Liu, Myco Le, Richard G. Baraniuk:
MalAlgoQA: Pedagogical Evaluation of Counterfactual Reasoning in Large Language Models and Implications for AI in Education. EMNLP (Findings) 2024: 15554-15567 - [c256]Lorenzo Luzi, Daniel LeJeune, Ali Siahkoohi, Sina Alemohammad, Vishwanath Saragadam, Hossein Babaei, Naiming Liu, Zichao Wang, Richard G. Baraniuk:
Titan: Bringing the Deep Image Prior to Implicit Representations. ICASSP 2024: 6165-6169 - [c255]Sina Alemohammad, Josue Casco-Rodriguez, Lorenzo Luzi, Ahmed Imtiaz Humayun, Hossein Babaei, Daniel LeJeune, Ali Siahkoohi, Richard G. Baraniuk:
Self-Consuming Generative Models Go MAD. ICLR 2024 - [c254]T. Mitchell Roddenberry, Vishwanath Saragadam, Maarten V. de Hoop, Richard G. Baraniuk:
Implicit Neural Representations and the Algebra of Complex Wavelets. ICLR 2024 - [c253]Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk:
Deep Networks Always Grok and Here is Why. ICML 2024 - [c252]Tam Minh Nguyen, César A. Uribe, Tan Minh Nguyen, Richard G. Baraniuk:
PIDformer: Transformer Meets Control Theory. ICML 2024 - [c251]Shashank Sonkar, Xinghe Chen, Myco Le, Naiming Liu, Debshila Basu Mallick, Richard G. Baraniuk:
Code Soliloquies for Accurate Calculations in Large Language Models. LAK 2024: 828-835 - [i175]Josue Casco-Rodriguez, Caleb Kemere, Richard G. Baraniuk:
[Re] The Discriminative Kalman Filter for Bayesian Filtering with Nonlinear and Non-Gaussian Observation Models. CoRR abs/2401.14429 (2024) - [i174]Shashank Sonkar, Kangqi Ni, Sapana Chaudhary, Richard G. Baraniuk:
Pedagogical Alignment of Large Language Models. CoRR abs/2402.05000 (2024) - [i173]Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk:
Deep Networks Always Grok and Here is Why. CoRR abs/2402.15555 (2024) - [i172]Tam Nguyen, César A. Uribe, Tan M. Nguyen, Richard G. Baraniuk:
PIDformer: Transformer Meets Control Theory. CoRR abs/2402.15989 (2024) - [i171]Shashank Sonkar, Naiming Liu, Debshila Basu Mallick, Richard G. Baraniuk:
Marking: Visual Grading with Highlighting Errors and Annotating Missing Bits. CoRR abs/2404.14301 (2024) - [i170]Shashank Sonkar, Kangqi Ni, Lesa Tran Lu, Kristi Kincaid, John S. Hutchinson, Richard G. Baraniuk:
Automated Long Answer Grading with RiceChem Dataset. CoRR abs/2404.14316 (2024) - [i169]Shashank Sonkar, Naiming Liu, Richard G. Baraniuk:
Regressive Side Effects of Training Language Models to Mimic Student Misconceptions. CoRR abs/2404.15156 (2024) - [i168]Shashank Sonkar, Richard G. Baraniuk:
Many-Shot Regurgitation (MSR) Prompting. CoRR abs/2405.08134 (2024) - [i167]Paul M. Mayer, Lorenzo Luzi, Ali Siahkoohi, Don H. Johnson, Richard G. Baraniuk:
Removing Bias from Maximum Likelihood Estimation with Model Autophagy. CoRR abs/2405.13977 (2024) - [i166]Omer Ronen, Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk, Bin Yu:
ScaLES: Scalable Latent Exploration Score for Pre-Trained Generative Networks. CoRR abs/2406.09657 (2024) - [i165]Naiming Liu, Zichao Wang, Richard G. Baraniuk:
Synthetic Context Generation for Question Generation. CoRR abs/2406.13188 (2024) - [i164]Tan M. Nguyen, Tam Nguyen, Nhat Ho, Andrea L. Bertozzi, Richard G. Baraniuk, Stanley J. Osher:
A Primal-Dual Framework for Transformers and Neural Networks. CoRR abs/2406.13781 (2024) - [i163]Naiming Liu, Shashank Sonkar, Myco Le, Richard G. Baraniuk:
MalAlgoQA: A Pedagogical Approach for Evaluating Counterfactual Reasoning Abilities. CoRR abs/2407.00938 (2024) - [i162]Randall Balestriero, Ahmed Imtiaz Humayun, Richard G. Baraniuk:
On the Geometry of Deep Learning. CoRR abs/2408.04809 (2024) - [i161]Sina Alemohammad, Ahmed Imtiaz Humayun, Shruti Agarwal, John P. Collomosse, Richard G. Baraniuk:
Self-Improving Diffusion Models with Synthetic Data. CoRR abs/2408.16333 (2024) - [i160]Kushal Vyas, Ahmed Imtiaz Humayun, Aniket Dashpute, Richard G. Baraniuk, Ashok Veeraraghavan, Guha Balakrishnan:
Learning Transferable Features for Implicit Neural Representations. CoRR abs/2409.09566 (2024) - [i159]Shashank Sonkar, Xinghe Chen, Naiming Liu, Richard G. Baraniuk, Mrinmaya Sachan:
LLM-based Cognitive Models of Students with Misconceptions. CoRR abs/2410.12294 (2024) - [i158]Gabriel Díaz-Ramos, Toros Arikan, Richard G. Baraniuk:
MazeNet: An Accurate, Fast, and Scalable Deep Learning Solution for Steiner Minimum Trees. CoRR abs/2410.18832 (2024) - 2023
- [j118]Fernando Gama, Nicolas Zilberstein, Martin Sevilla, Richard G. Baraniuk, Santiago Segarra:
Unsupervised Learning of Sampling Distributions for Particle Filters. IEEE Trans. Signal Process. 71: 3852-3866 (2023) - [c250]Vincent Aleven, Richard G. Baraniuk, Emma Brunskill, Scott Crossley, Dora Demszky, Stephen Fancsali, Shivang Gupta, Kenneth R. Koedinger, Chris Piech, Steven Ritter, Danielle R. Thomas, Simon Woodhead, Wanli Xing:
Towards the Future of AI-Augmented Human Tutoring in Math Learning. AIED (Posters/Late Breaking Results/...) 2023: 26-31 - [c249]Shashank Sonkar, Richard G. Baraniuk:
Deduction under Perturbed Evidence: Probing Student Simulation (Knowledge Tracing) Capabilities of Large Language Models. LLM@AIED 2023: 26-33 - [c248]Katie Bainbridge, Candace A. Walkington, Armon Ibrahim, Iris Zhong, Debshila Basu Mallick, Julianna Washington, Richard G. Baraniuk:
A Case Study using Large Language Models to Generate Metadata for Math Questions. LLM@AIED 2023: 34-42 - [c247]Jasper Tan, Daniel LeJeune, Blake Mason, Hamid Javadi, Richard G. Baraniuk:
A Blessing of Dimensionality in Membership Inference through Regularization. AISTATS 2023: 10968-10993 - [c246]Zichao Wang, Richard G. Baraniuk:
MultiQG-TI: Towards Question Generation from Multi-modal Sources. BEA@ACL 2023: 682-691 - [c245]Ahmed Imtiaz Humayun, Randall Balestriero, Guha Balakrishnan, Richard G. Baraniuk:
SplineCam: Exact Visualization and Characterization of Deep Network Geometry and Decision Boundaries. CVPR 2023: 3789-3798 - [c244]Vishwanath Saragadam, Daniel LeJeune, Jasper Tan, Guha Balakrishnan, Ashok Veeraraghavan, Richard G. Baraniuk:
WIRE: Wavelet Implicit Neural Representations. CVPR 2023: 18507-18516 - [c243]Shashank Sonkar, Naiming Liu, Debshila Basu Mallick, Richard G. Baraniuk:
CLASS: A Design Framework for Building Intelligent Tutoring Systems Based on Learning Science principles. EMNLP (Findings) 2023: 1941-1961 - [c242]Tan M. Nguyen, Tam Nguyen, Long Bui, Hai Do, Duy Khuong Nguyen, Dung D. Le, Hung Tran-The, Nhat Ho, Stanley J. Osher, Richard G. Baraniuk:
A Probabilistic Framework for Pruning Transformers Via a Finite Admixture of Keys. ICASSP 2023: 1-5 - [c241]Zichao Wang, Weili Nie, Zhuoran Qiao, Chaowei Xiao, Richard G. Baraniuk, Anima Anandkumar:
Retrieval-based Controllable Molecule Generation. ICLR 2023 - [c240]Tan Minh Nguyen, Tam Minh Nguyen, Nhat Ho, Andrea L. Bertozzi, Richard G. Baraniuk, Stanley J. Osher:
A Primal-Dual Framework for Transformers and Neural Networks. ICLR 2023 - [c239]Steven Ritter, Neil T. Heffernan, Joseph Jay Williams, Derek Lomas, Klinton Bicknell, Jeremy Roschelle, Ben Motz, Danielle S. McNamara, Richard G. Baraniuk, Debshila Basu Mallick, René F. Kizilcec, Ryan Baker, Stephen Fancsali, April Murphy:
Fourth Annual Workshop on A/B Testing and Platform-Enabled Learning Research. L@S 2023: 254-256 - [c238]Debshila Basu Mallick, Brittany C. Bradford, Richard G. Baraniuk:
Secure Education and Learning Research at Scale with OpenStax Kinetic. L@S 2023: 360-362 - [c237]Brittany C. Bradford, Debshila Basu Mallick, Richard G. Baraniuk:
Unlocking Financial Success: Empowering Higher Ed Students and Developing Financial Literacy Interventions at Scale. L@S 2023: 363-367 - [c236]Tam Nguyen, Tan Nguyen, Richard G. Baraniuk:
Mitigating Over-smoothing in Transformers via Regularized Nonlocal Functionals. NeurIPS 2023 - [c235]Shashank Sonkar, Zichao Wang, Richard G. Baraniuk:
MANER: Mask Augmented Named Entity Recognition for Extreme Low-Resource Languages. SustaiNLP 2023: 219-226 - [c234]Lorenzo Luzi, Carlos Ortiz Marrero, Nile Wynar, Richard G. Baraniuk, Michael J. Henry:
Evaluating generative networks using Gaussian mixtures of image features. WACV 2023: 279-288 - [i157]Vishwanath Saragadam, Daniel LeJeune, Jasper Tan, Guha Balakrishnan, Ashok Veeraraghavan, Richard G. Baraniuk:
WIRE: Wavelet Implicit Neural Representations. CoRR abs/2301.05187 (2023) - [i156]Ahmed Imtiaz Humayun, Randall Balestriero, Guha Balakrishnan, Richard G. Baraniuk:
SplineCam: Exact Visualization and Characterization of Deep Network Geometry and Decision Boundaries. CoRR abs/2302.12828 (2023) - [i155]Shashank Sonkar, Lucy Liu, Debshila Basu Mallick, Richard G. Baraniuk:
CLASS Meet SPOCK: An Education Tutoring Chatbot based on Learning Science Principles. CoRR abs/2305.13272 (2023) - [i154]Shashank Sonkar, Richard G. Baraniuk:
Investigating the Role of Feed-Forward Networks in Transformers Using Parallel Attention and Feed-Forward Net Design. CoRR abs/2305.13297 (2023) - [i153]Shashank Sonkar, Richard G. Baraniuk:
Deduction under Perturbed Evidence: Probing Student Simulation Capabilities of Large Language Models. CoRR abs/2305.14507 (2023) - [i152]Sina Alemohammad, Josue Casco-Rodriguez, Lorenzo Luzi, Ahmed Imtiaz Humayun, Hossein Babaei, Daniel LeJeune, Ali Siahkoohi, Richard G. Baraniuk:
Self-Consuming Generative Models Go MAD. CoRR abs/2307.01850 (2023) - [i151]Zichao Wang, Richard G. Baraniuk:
MultiQG-TI: Towards Question Generation from Multi-modal Sources. CoRR abs/2307.04643 (2023) - [i150]Shashank Sonkar, Myco Le, Xinghe Chen, Naiming Liu, Debshila Basu Mallick, Richard G. Baraniuk:
Code Soliloquies for Accurate Calculations in Large Language Models. CoRR abs/2309.12161 (2023) - [i149]T. Mitchell Roddenberry, Vishwanath Saragadam, Maarten V. de Hoop, Richard G. Baraniuk:
Implicit Neural Representations and the Algebra of Complex Wavelets. CoRR abs/2310.00545 (2023) - [i148]Naiming Liu, Shashank Sonkar, Zichao Wang, Simon Woodhead, Richard G. Baraniuk:
Novice Learner and Expert Tutor: Evaluating Math Reasoning Abilities of Large Language Models with Misconceptions. CoRR abs/2310.02439 (2023) - [i147]Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk:
Training Dynamics of Deep Network Linear Regions. CoRR abs/2310.12977 (2023) - [i146]Tam Nguyen, Tan M. Nguyen, Richard G. Baraniuk:
Mitigating Over-smoothing in Transformers via Regularized Nonlocal Functionals. CoRR abs/2312.00751 (2023) - [i145]Micah Goldblum, Anima Anandkumar, Richard G. Baraniuk, Tom Goldstein, Kyunghyun Cho, Zachary C. Lipton, Melanie Mitchell, Preetum Nakkiran, Max Welling, Andrew Gordon Wilson:
Perspectives on the State and Future of Deep Learning - 2023. CoRR abs/2312.09323 (2023) - 2022
- [j117]David J. Brenes, C. J. Barberan, Brady Hunt, Sonia G. Parra, Mila P. Salcedo, Júlio C. Possati-Resende, Miriam L. Cremer, Philip E. Castle, José H. T. G. Fregnani, Mauricio Maza, Kathleen M. Schmeler, Richard G. Baraniuk, Rebecca R. Richards-Kortum:
Multi-task network for automated analysis of high-resolution endomicroscopy images to detect cervical precancer and cancer. Comput. Medical Imaging Graph. 97: 102052 (2022) - [j116]Ali Mousavi, Richard G. Baraniuk:
Uniform Partitioning of Data Grid for Association Detection. IEEE Trans. Pattern Anal. Mach. Intell. 44(2): 1098-1107 (2022) - [j115]Bao Wang, Tan M. Nguyen, Tao Sun, Andrea L. Bertozzi, Richard G. Baraniuk, Stanley J. Osher:
Scheduled Restart Momentum for Accelerated Stochastic Gradient Descent. SIAM J. Imaging Sci. 15(2): 738-761 (2022) - [j114]Yehuda Dar, Richard G. Baraniuk:
Double Double Descent: On Generalization Errors in Transfer Learning between Linear Regression Tasks. SIAM J. Math. Data Sci. 4(4): 1447-1472 (2022) - [j113]Ángel Bueno Rodríguez, Randall Balestriero, Silvio De Angelis, M. Carmen Benítez, Luciano Zuccarello, Richard G. Baraniuk, Jesús M. Ibáñez, Maarten V. de Hoop:
Recurrent Scattering Network Detects Metastable Behavior in Polyphonic Seismo-Volcanic Signals for Volcano Eruption Forecasting. IEEE Trans. Geosci. Remote. Sens. 60: 1-23 (2022) - [j112]Haoran You, Randall Balestriero, Zhihan Lu, Yutong Kou, Huihong Shi, Shunyao Zhang, Shang Wu, Yingyan Lin, Richard G. Baraniuk:
Max-Affine Spline Insights Into Deep Network Pruning. Trans. Mach. Learn. Res. 2022 (2022) - [j111]Pavan K. Kota, Daniel LeJeune, Rebekah A. Drezek, Richard G. Baraniuk:
Extreme Compressed Sensing of Poisson Rates From Multiple Measurements. IEEE Trans. Signal Process. 70: 2388-2401 (2022) - [j110]T. Mitchell Roddenberry, Fernando Gama, Richard G. Baraniuk, Santiago Segarra:
On Local Distributions in Graph Signal Processing. IEEE Trans. Signal Process. 70: 5564-5577 (2022) - [c233]Romain Cosentino, Randall Balestriero, Yanis Bahroun, Anirvan M. Sengupta, Richard G. Baraniuk, Behnaam Aazhang:
Spatial Transformer K-Means. IEEECONF 2022: 1444-1448 - [c232]Zichao Wang, Jakob Valdez, Debshila Basu Mallick, Richard G. Baraniuk:
Towards Human-Like Educational Question Generation with Large Language Models. AIED (1) 2022: 153-166 - [c231]Nigel Fernandez, Aritra Ghosh, Naiming Liu, Zichao Wang, Benoît Choffin, Richard G. Baraniuk, Andrew S. Lan:
Automated Scoring for Reading Comprehension via In-context BERT Tuning. AIED (1) 2022: 691-697 - [c230]Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk:
Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values. CVPR 2022: 10631-10640 - [c229]Gowthami Somepalli, Liam Fowl, Arpit Bansal, Ping-Yeh Chiang, Yehuda Dar, Richard G. Baraniuk, Micah Goldblum, Tom Goldstein:
Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective. CVPR 2022: 13689-13698 - [c228]Vishwanath Saragadam, Jasper Tan, Guha Balakrishnan, Richard G. Baraniuk, Ashok Veeraraghavan:
MINER: Multiscale Implicit Neural Representation. ECCV (23) 2022: 318-333 - [c227]Naiming Liu, Zichao Wang, Richard G. Baraniuk, Andrew S. Lan:
Open-ended Knowledge Tracing for Computer Science Education. EMNLP 2022: 3849-3862 - [c226]C. J. Barberan, Sina Alemmohammad, Naiming Liu, Randall Balestriero, Richard G. Baraniuk:
NeuroView-RNN: It's About Time. FAccT 2022: 1683-1697 - [c225]Sina Alemohammad, Hossein Babaei, C. J. Barberan, Naiming Liu, Lorenzo Luzi, Blake Mason, Richard G. Baraniuk:
NFT-K: Non-Fungible Tangent Kernels. ICASSP 2022: 3798-3802 - [c224]Randall Balestriero, Zichao Wang, Richard G. Baraniuk:
DeepHull: Fast Convex Hull Approximation in High Dimensions. ICASSP 2022: 3888-3892 - [c223]Ahmed Imtiaz Humayun, Randall Balestriero, Anastasios Kyrillidis, Richard G. Baraniuk:
No More Than 6ft Apart: Robust K-Means via Radius Upper Bounds. ICASSP 2022: 4433-4437 - [c222]Fernando Gama, Nicolas Zilberstein, Richard G. Baraniuk, Santiago Segarra:
Unrolling Particles: Unsupervised Learning of Sampling Distributions. ICASSP 2022: 5498-5502 - [c221]Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk:
MaGNET: Uniform Sampling from Deep Generative Network Manifolds Without Retraining. ICLR 2022 - [c220]Tam Minh Nguyen, Tan Minh Nguyen, Dung D. D. Le, Duy Khuong Nguyen, Viet-Anh Tran, Richard G. Baraniuk, Nhat Ho, Stanley J. Osher:
Improving Transformers with Probabilistic Attention Keys. ICML 2022: 16595-16621 - [c219]Steven Ritter, Neil T. Heffernan, Joseph Jay Williams, Derek Lomas, Ben Motz, Debshila Basu Mallick, Klinton Bicknell, Danielle S. McNamara, René F. Kizilcec, Jeremy Roschelle, Richard G. Baraniuk, Ryan Baker:
Third Annual Workshop on A/B Testing and Platform-Enabled Learning Research. L@S 2022: 252-254 - [c218]Tan Minh Nguyen, Richard G. Baraniuk, Robert M. Kirby, Stanley J. Osher, Bao Wang:
Momentum Transformer: Closing the Performance Gap Between Self-attention and Its Linearization. MSML 2022: 189-204 - [c217]Jasper Tan, Blake Mason, Hamid Javadi, Richard G. Baraniuk:
Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference. NeurIPS 2022 - [i144]Jasper Tan, Blake Mason, Hamid Javadi, Richard G. Baraniuk:
Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference. CoRR abs/2202.01243 (2022) - [i143]Vishwanath Saragadam, Jasper Tan, Guha Balakrishnan, Richard G. Baraniuk, Ashok Veeraraghavan:
MINER: Multiscale Implicit Neural Representations. CoRR abs/2202.03532 (2022) - [i142]Romain Cosentino, Randall Balestriero, Yanis Bahroun, Anirvan M. Sengupta, Richard G. Baraniuk, Behnaam Aazhang:
Spatial Transformer K-Means. CoRR abs/2202.07829 (2022) - [i141]T. Mitchell Roddenberry, Fernando Gama, Richard G. Baraniuk, Santiago Segarra:
On Local Distributions in Graph Signal Processing. CoRR abs/2202.10649 (2022) - [i140]C. J. Barberan, Sina Alemohammad, Naiming Liu, Randall Balestriero, Richard G. Baraniuk:
NeuroView-RNN: It's About Time. CoRR abs/2202.11811 (2022) - [i139]Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk:
Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values. CoRR abs/2203.01993 (2022) - [i138]Ahmed Imtiaz Humayun, Randall Balestriero, Anastasios Kyrillidis, Richard G. Baraniuk:
No More Than 6ft Apart: Robust K-Means via Radius Upper Bounds. CoRR abs/2203.02502 (2022) - [i137]Rudolf H. Riedi, Randall Balestriero, Richard G. Baraniuk:
Singular Value Perturbation and Deep Network Optimization. CoRR abs/2203.03099 (2022) - [i136]Naiming Liu, Zichao Wang, Richard G. Baraniuk, Andrew S. Lan:
Open-Ended Knowledge Tracing. CoRR abs/2203.03716 (2022) - [i135]Gowthami Somepalli, Liam Fowl, Arpit Bansal, Ping-Yeh Chiang, Yehuda Dar, Richard G. Baraniuk, Micah Goldblum, Tom Goldstein:
Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective. CoRR abs/2203.08124 (2022) - [i134]Vishwanath Saragadam, Randall Balestriero, Ashok Veeraraghavan, Richard G. Baraniuk:
DeepTensor: Low-Rank Tensor Decomposition with Deep Network Priors. CoRR abs/2204.03145 (2022) - [i133]Nigel Fernandez, Aritra Ghosh, Naiming Liu, Zichao Wang, Benoît Choffin, Richard G. Baraniuk, Andrew S. Lan:
Automated Scoring for Reading Comprehension via In-context BERT Tuning. CoRR abs/2205.09864 (2022) - [i132]Jasper Tan, Daniel LeJeune, Blake Mason, Hamid Javadi, Richard G. Baraniuk:
Benign Overparameterization in Membership Inference with Early Stopping. CoRR abs/2205.14055 (2022) - [i131]Tan M. Nguyen, Richard G. Baraniuk, Robert M. Kirby, Stanley J. Osher, Bao Wang:
Momentum Transformer: Closing the Performance Gap Between Self-attention and Its Linearization. CoRR abs/2208.00579 (2022) - [i130]Zichao Wang, Weili Nie, Zhuoran Qiao, Chaowei Xiao, Richard G. Baraniuk, Anima Anandkumar:
Retrieval-based Controllable Molecule Generation. CoRR abs/2208.11126 (2022) - [i129]Randall Balestriero, Richard G. Baraniuk:
Batch Normalization Explained. CoRR abs/2209.14778 (2022) - [i128]Lorenzo Luzi, Ali Siahkoohi, Paul M. Mayer, Josue Casco-Rodriguez, Richard G. Baraniuk:
Boomerang: Local sampling on image manifolds using diffusion models. CoRR abs/2210.12100 (2022) - [i127]Shashank Sonkar, Naiming Liu, Richard G. Baraniuk:
A Visual Tour Of Current Challenges In Multimodal Language Models. CoRR abs/2210.12565 (2022) - [i126]Daniel LeJeune, Pratik Patil, Hamid Javadi, Richard G. Baraniuk, Ryan J. Tibshirani:
Asymptotics of the Sketched Pseudoinverse. CoRR abs/2211.03751 (2022) - [i125]Yehuda Dar, Lorenzo Luzi, Richard G. Baraniuk:
Overfreezing Meets Overparameterization: A Double Descent Perspective on Transfer Learning of Deep Neural Networks. CoRR abs/2211.11074 (2022) - [i124]Vishwanath Saragadam, Zheyi Han, Vivek Boominathan, Luocheng Huang, Shiyu Tan, Johannes E. Fröch, Karl F. Böhringer, Richard G. Baraniuk, Arka Majumdar, Ashok Veeraraghavan:
Foveated Thermal Computational Imaging in the Wild Using All-Silicon Meta-Optics. CoRR abs/2212.06345 (2022) - [i123]Shashank Sonkar, Zichao Wang, Richard G. Baraniuk:
MANER: Mask Augmented Named Entity Recognition for Extreme Low-Resource Languages. CoRR abs/2212.09723 (2022) - 2021
- [j109]Vishwanath Saragadam, Michael DeZeeuw, Richard G. Baraniuk, Ashok Veeraraghavan, Aswin C. Sankaranarayanan:
SASSI - Super-Pixelated Adaptive Spatio-Spectral Imaging. IEEE Trans. Pattern Anal. Mach. Intell. 43(7): 2233-2244 (2021) - [j108]Randall Balestriero, Richard G. Baraniuk:
Mad Max: Affine Spline Insights Into Deep Learning. Proc. IEEE 109(5): 704-727 (2021) - [j107]Nathan Dunkelberger, Jennifer L. Sullivan, Joshua Bradley, Indu Manickam, Gautam Dasarathy, Richard G. Baraniuk, Marcia K. O'Malley:
A Multisensory Approach to Present Phonemes as Language Through a Wearable Haptic Device. IEEE Trans. Haptics 14(1): 188-199 (2021) - [c216]Zichao Wang, Sebastian Tschiatschek, Simon Woodhead, José Miguel Hernández-Lobato, Simon Peyton Jones, Richard G. Baraniuk, Cheng Zhang:
Educational Question Mining At Scale: Prediction, Analysis and Personalization. AAAI 2021: 15669-15677 - [c215]Andrew E. Waters, Vinay K. Chaudhri, Debshila Basu Mallick, Richard G. Baraniuk:
A Relationship Selection Task (short paper). iTextbooks@AIED 2021: 88-92 - [c214]Zichao Wang, Andrew S. Lan, Richard G. Baraniuk:
Mathematical Formula Representation via Tree Embeddings. iTextbooks@AIED 2021: 121-133 - [c213]Zichao Wang, Kyle Manning, Debshila Basu Mallick, Richard G. Baraniuk:
Towards Blooms Taxonomy Classification Without Labels. AIED (1) 2021: 433-445 - [c212]Vinay K. Chaudhri, Matthew Boggess, Han Lin Aung, Debshila Basu Mallick, Andrew C. Waters, Richard G. Baraniuk:
A Case Study in Bootstrapping Ontology Graphs from Textbooks. AKBC 2021 - [c211]Tianyi Yao, Daniel LeJeune, Hamid Javadi, Richard G. Baraniuk, Genevera I. Allen:
Minipatch Learning as Implicit Ridge-Like Regularization. BigComp 2021: 65-68 - [c210]Zichao Wang, Mengxue Zhang, Richard G. Baraniuk, Andrew S. Lan:
Scientific Formula Retrieval via Tree Embeddings. IEEE BigData 2021: 1493-1503 - [c209]Mengxue Zhang, Zichao Wang, Richard G. Baraniuk, Andrew S. Lan:
Math Operation Embeddings for Open-ended Solution Analysis and Feedback. EDM 2021 - [c208]Zichao Wang, Andrew S. Lan, Richard G. Baraniuk:
Math Word Problem Generation with Mathematical Consistency and Problem Context Constraints. EMNLP (1) 2021: 5986-5999 - [c207]Sina Alemohammad, Hossein Babaei, Randall Balestriero, Matt Y. Cheung, Ahmed Imtiaz Humayun, Daniel LeJeune, Naiming Liu, Lorenzo Luzi, Jasper Tan, Zichao Wang, Richard G. Baraniuk:
Wearing A Mask: Compressed Representations of Variable-Length Sequences Using Recurrent Neural Tangent Kernels. ICASSP 2021: 2950-2954 - [c206]Vishwanath Saragadam, Akshat Dave, Ashok Veeraraghavan, Richard G. Baraniuk:
Thermal Image Processing via Physics-Inspired Deep Networks. ICCVW 2021: 4040-4048 - [c205]Sina Alemohammad, Zichao Wang, Randall Balestriero, Richard G. Baraniuk:
The Recurrent Neural Tangent Kernel. ICLR 2021 - [c204]Shashank Sonkar, Arzoo Katiyar, Richard G. Baraniuk:
NePTuNe: Neural Powered Tucker Networkfor Knowledge Graph Completion. IJCKG 2021: 177-180 - [c203]Randall Balestriero, Hervé Glotin, Richard G. Baraniuk:
Interpretable and Learnable Super-Resolution Time-Frequency Representation. MSML 2021: 118-152 - [c202]Romain Cosentino, Randall Balestriero, Richard G. Baraniuk, Behnaam Aazhang:
Deep Autoencoders: From Understanding to Generalization Guarantees. MSML 2021: 197-222 - [c201]Daniel LeJeune, Hamid Javadi, Richard G. Baraniuk:
The Flip Side of the Reweighted Coin: Duality of Adaptive Dropout and Regularization. NeurIPS 2021: 23401-23412 - [e3]Sergey A. Sosnovsky, Peter Brusilovsky, Richard G. Baraniuk, Andrew S. Lan:
Proceedings of the Third International Workshop on Inteligent Textbooks 2021 Co-located with 22nd International Conference on Artificial Intelligence in Education (AIED 2021), Online, June 15, 2021. CEUR Workshop Proceedings 2895, CEUR-WS.org 2021 [contents] - [i122]Randall Balestriero, Haoran You, Zhihan Lu, Yutong Kou, Yingyan Lin, Richard G. Baraniuk:
Max-Affine Spline Insights Into Deep Network Pruning. CoRR abs/2101.02338 (2021) - [i121]Yehuda Dar, Richard G. Baraniuk:
Transfer Learning Can Outperform the True Prior in Double Descent Regularization. CoRR abs/2103.05621 (2021) - [i120]Randall Balestriero, Richard G. Baraniuk:
Fast Jacobian-Vector Product for Deep Networks. CoRR abs/2104.00219 (2021) - [i119]Zichao Wang, Angus Lamb, Evgeny Saveliev, Pashmina Cameron, Yordan Zaykov, José Miguel Hernández-Lobato, Richard E. Turner, Richard G. Baraniuk, Craig Barton, Simon Peyton Jones, Simon Woodhead, Cheng Zhang:
Results and Insights from Diagnostic Questions: The NeurIPS 2020 Education Challenge. CoRR abs/2104.04034 (2021) - [i118]Shashank Sonkar, Arzoo Katiyar, Richard G. Baraniuk:
NePTuNe: Neural Powered Tucker Network for Knowledge Graph Completion. CoRR abs/2104.07824 (2021) - [i117]Mengxue Zhang, Zichao Wang, Richard G. Baraniuk, Andrew S. Lan:
Math Operation Embeddings for Open-ended Solution Analysis and Feedback. CoRR abs/2104.12047 (2021) - [i116]Lorenzo Luzi, Yehuda Dar, Richard G. Baraniuk:
Double Descent and Other Interpolation Phenomena in GANs. CoRR abs/2106.04003 (2021) - [i115]Daniel LeJeune, Hamid Javadi, Richard G. Baraniuk:
The Flip Side of the Reweighted Coin: Duality of Adaptive Dropout and Regularization. CoRR abs/2106.07769 (2021) - [i114]Vishwanath Saragadam, Akshat Dave, Ashok Veeraraghavan, Richard G. Baraniuk:
Thermal Image Processing via Physics-Inspired Deep Networks. CoRR abs/2108.07973 (2021) - [i113]Yehuda Dar, Vidya Muthukumar, Richard G. Baraniuk:
A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning. CoRR abs/2109.02355 (2021) - [i112]Zichao Wang, Andrew S. Lan, Richard G. Baraniuk:
Math Word Problem Generation with Mathematical Consistency and Problem Context Constraints. CoRR abs/2109.04546 (2021) - [i111]Fernando Gama, Nicolas Zilberstein, Richard G. Baraniuk, Santiago Segarra:
Unrolling Particles: Unsupervised Learning of Sampling Distributions. CoRR abs/2110.02915 (2021) - [i110]Sina Alemohammad, Hossein Babaei, C. J. Barberan, Naiming Liu, Lorenzo Luzi, Blake Mason, Richard G. Baraniuk:
NFT-K: Non-Fungible Tangent Kernels. CoRR abs/2110.04945 (2021) - [i109]Lorenzo Luzi, Carlos Ortiz Marrero, Nile Wynar, Richard G. Baraniuk, Michael J. Henry:
Evaluating generative networks using Gaussian mixtures of image features. CoRR abs/2110.05240 (2021) - [i108]C. J. Barberan, Randall Balestriero, Richard G. Baraniuk:
NeuroView: Explainable Deep Network Decision Making. CoRR abs/2110.07778 (2021) - [i107]Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk:
MaGNET: Uniform Sampling from Deep Generative Network Manifolds Without Retraining. CoRR abs/2110.08009 (2021) - [i106]Tam Nguyen, Tan M. Nguyen, Dung Le, Khuong Nguyen, Anh Tran, Richard G. Baraniuk, Nhat Ho, Stanley J. Osher:
Transformer with a Mixture of Gaussian Keys. CoRR abs/2110.08678 (2021) - 2020
- [j106]Richard G. Baraniuk, Alex Dimakis, Negar Kiyavash, Sewoong Oh, Rebecca Willett:
Guest Editorial. IEEE J. Sel. Areas Inf. Theory 1(1): 4 (2020) - [j105]Gregory Ongie, Ajil Jalal, Christopher A. Metzler, Richard G. Baraniuk, Alexandros G. Dimakis, Rebecca Willett:
Deep Learning Techniques for Inverse Problems in Imaging. IEEE J. Sel. Areas Inf. Theory 1(1): 39-56 (2020) - [j104]Yue Wang, Jianghao Shen, Ting-Kuei Hu, Pengfei Xu, Tan M. Nguyen, Richard G. Baraniuk, Zhangyang Wang, Yingyan Lin:
Dual Dynamic Inference: Enabling More Efficient, Adaptive, and Controllable Deep Inference. IEEE J. Sel. Top. Signal Process. 14(4): 623-633 (2020) - [j103]Richard G. Baraniuk, David L. Donoho, Matan Gavish:
The science of deep learning. Proc. Natl. Acad. Sci. USA 117(48): 30029-30032 (2020) - [j102]Romain Cosentino, Randall Balestriero, Richard G. Baraniuk, Behnaam Aazhang:
Universal Frame Thresholding. IEEE Signal Process. Lett. 27: 1115-1119 (2020) - [j101]Manoj Kumar Sharma, Christopher A. Metzler, Sudarshan Nagesh, Richard G. Baraniuk, Oliver Cossairt, Ashok Veeraraghavan:
Inverse Scattering via Transmission Matrices: Broadband Illumination and Fast Phase Retrieval Algorithms. IEEE Trans. Computational Imaging 6: 95-108 (2020) - [c200]David Y. J. Kim, Adam Winchell, Andrew E. Waters, Phillip Grimaldi, Richard G. Baraniuk, Michael Mozer:
Inferring Student Comprehension from Highlighting Patterns in Digital Textbooks: An Exploration in an Authentic Learning Platform. iTextbooks@AIED 2020: 67-79 - [c199]Daniel LeJeune, Gautam Dasarathy, Richard G. Baraniuk:
Thresholding Graph Bandits with GrAPL. AISTATS 2020: 2476-2485 - [c198]Daniel LeJeune, Hamid Javadi, Richard G. Baraniuk:
The Implicit Regularization of Ordinary Least Squares Ensembles. AISTATS 2020: 3525-3535 - [c197]Shashank Sonkar, Andrew E. Waters, Richard G. Baraniuk:
Attention Word Embedding. COLING 2020: 6894-6902 - [c196]Zichao Wang, Yi Gu, Andrew S. Lan, Richard G. Baraniuk:
VarFA: A Variational Factor Analysis Framework For Efficient Bayesian Learning Analytics. EDM 2020 - [c195]Shashank Sonkar, Andrew S. Lan, Andrew E. Waters, Phillip Grimaldi, Richard G. Baraniuk:
qDKT: Question-centric Deep Knowledge Tracing. EDM 2020 - [c194]Haoran You, Chaojian Li, Pengfei Xu, Yonggan Fu, Yue Wang, Xiaohan Chen, Richard G. Baraniuk, Zhangyang Wang, Yingyan Lin:
Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks. ICLR 2020 - [c193]Jasper Tan, Salman Siddique Khan, Vivek Boominathan, Jeffrey Byrne, Richard G. Baraniuk, Kaushik Mitra, Ashok Veeraraghavan:
CANOPIC: Pre-Digital Privacy-Enhancing Encodings for Computer Vision. ICME 2020: 1-6 - [c192]Benjamin Coleman, Richard G. Baraniuk, Anshumali Shrivastava:
Sub-linear Memory Sketches for Near Neighbor Search on Streaming Data. ICML 2020: 2089-2099 - [c191]Yehuda Dar, Paul M. Mayer, Lorenzo Luzi, Richard G. Baraniuk:
Subspace Fitting Meets Regression: The Effects of Supervision and Orthonormality Constraints on Double Descent of Generalization Errors. ICML 2020: 2366-2375 - [c190]Zichao Wang, Angus Lamb, Evgeny Saveliev, Pashmina Cameron, Yordan Zaykov, José Miguel Hernández-Lobato, Richard E. Turner, Richard G. Baraniuk, Craig Barton, Simon Peyton Jones, Simon Woodhead, Cheng Zhang:
Results and Insights from Diagnostic Questions: The NeurIPS 2020 Education Challenge. NeurIPS (Competition and Demos) 2020: 191-205 - [c189]Randall Balestriero, Sébastien Paris, Richard G. Baraniuk:
Analytical Probability Distributions and Exact Expectation-Maximization for Deep Generative Networks. NeurIPS 2020 - [c188]Tan M. Nguyen, Richard G. Baraniuk, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang:
MomentumRNN: Integrating Momentum into Recurrent Neural Networks. NeurIPS 2020 - [e2]Sergey A. Sosnovsky, Peter Brusilovsky, Richard G. Baraniuk, Andrew S. Lan:
Proceedings of the Second International Workshop on Intelligent Textbooks 2020 co-located with 21st International Conference on Artificial Intelligence in Education (AIED 2020), Online, July 06, 2020. CEUR Workshop Proceedings 2674, CEUR-WS.org 2020 [contents] - [i105]Bao Wang, Tan M. Nguyen, Andrea L. Bertozzi, Richard G. Baraniuk, Stanley J. Osher:
Scheduled Restart Momentum for Accelerated Stochastic Gradient Descent. CoRR abs/2002.10583 (2020) - [i104]Yehuda Dar, Paul M. Mayer, Lorenzo Luzi, Richard G. Baraniuk:
Subspace Fitting Meets Regression: The Effects of Supervision and Orthonormality Constraints on Double Descent of Generalization Errors. CoRR abs/2002.10614 (2020) - [i103]Randall Balestriero, Sébastien Paris, Richard G. Baraniuk:
Max-Affine Spline Insights into Deep Generative Networks. CoRR abs/2002.11912 (2020) - [i102]Gregory Ongie, Ajil Jalal, Christopher A. Metzler, Richard G. Baraniuk, Alexandros G. Dimakis, Rebecca Willett:
Deep Learning Techniques for Inverse Problems in Imaging. CoRR abs/2005.06001 (2020) - [i101]Shashank Sonkar, Andrew E. Waters, Andrew S. Lan, Phillip J. Grimaldi, Richard G. Baraniuk:
qDKT: Question-centric Deep Knowledge Tracing. CoRR abs/2005.12442 (2020) - [i100]Jack Zichao Wang, Yi Gu, Andrew S. Lan, Richard G. Baraniuk:
VarFA: A Variational Factor Analysis Framework For Efficient Bayesian Learning Analytics. CoRR abs/2005.13107 (2020) - [i99]Shashank Sonkar, Andrew E. Waters, Richard G. Baraniuk:
Attention Word Embedding. CoRR abs/2006.00988 (2020) - [i98]Tan M. Nguyen, Richard G. Baraniuk, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang:
MomentumRNN: Integrating Momentum into Recurrent Neural Networks. CoRR abs/2006.06919 (2020) - [i97]Yehuda Dar, Richard G. Baraniuk:
Double Double Descent: On Generalization Errors in Transfer Learning between Linear Regression Tasks. CoRR abs/2006.07002 (2020) - [i96]Weili Nie, Zichao Wang, Ankit B. Patel, Richard G. Baraniuk:
An Improved Semi-Supervised VAE for Learning Disentangled Representations. CoRR abs/2006.07460 (2020) - [i95]Randall Balestriero, Hervé Glotin, Richard G. Baraniuk:
Interpretable Super-Resolution via a Learned Time-Series Representation. CoRR abs/2006.07713 (2020) - [i94]Randall Balestriero, Sébastien Paris, Richard G. Baraniuk:
Analytical Probability Distributions and EM-Learning for Deep Generative Networks. CoRR abs/2006.10023 (2020) - [i93]Sina Alemohammad, Zichao Wang, Randall Balestriero, Richard G. Baraniuk:
The Recurrent Neural Tangent Kernel. CoRR abs/2006.10246 (2020) - [i92]Lorenzo Luzi, Randall Balestriero, Richard G. Baraniuk:
Ensembles of Generative Adversarial Networks for Disconnected Data. CoRR abs/2006.14600 (2020) - [i91]Rajeev Alur, Richard G. Baraniuk, Rastislav Bodík, Ann W. Drobnis, Sumit Gulwani, Bjoern Hartmann, Yasmin B. Kafai, Jeff Karpicke, Ran Libeskind-Hadas, Debra J. Richardson, Armando Solar-Lezama, Candace Thille, Moshe Y. Vardi:
Computer-Aided Personalized Education. CoRR abs/2007.03704 (2020) - [i90]Zichao Wang, Angus Lamb, Evgeny Saveliev, Pashmina Cameron, Yordan Zaykov, José Miguel Hernández-Lobato, Richard E. Turner, Richard G. Baraniuk, Craig Barton, Simon Peyton Jones, Simon Woodhead, Cheng Zhang:
Diagnostic Questions: The NeurIPS 2020 Education Challenge. CoRR abs/2007.12061 (2020) - [i89]Romain Cosentino, Randall Balestriero, Richard G. Baraniuk, Behnaam Aazhang:
Provable Finite Data Generalization with Group Autoencoder. CoRR abs/2009.09525 (2020) - [i88]Sina Alemohammad, Hossein Babaei, Randall Balestriero, Matt Y. Cheung, Ahmed Imtiaz Humayun, Daniel LeJeune, Naiming Liu, Lorenzo Luzi, Jasper Tan, Zichao Wang, Richard G. Baraniuk:
Wearing a MASK: Compressed Representations of Variable-Length Sequences Using Recurrent Neural Tangent Kernels. CoRR abs/2010.13975 (2020) - [i87]Sina Alemohammad, Randall Balestriero, Zichao Wang, Richard G. Baraniuk:
Scalable Neural Tangent Kernel of Recurrent Architectures. CoRR abs/2012.04859 (2020) - [i86]Romain Cosentino, Randall Balestriero, Yanis Bahroun, Anirvan M. Sengupta, Richard G. Baraniuk, Behnaam Aazhang:
Interpretable Image Clustering via Diffeomorphism-Aware K-Means. CoRR abs/2012.09743 (2020) - [i85]Vishwanath Saragadam, Michael DeZeeuw, Richard G. Baraniuk, Ashok Veeraraghavan, Aswin C. Sankaranarayanan:
SASSI - Super-Pixelated Adaptive Spatio-Spectral Imaging. CoRR abs/2012.14495 (2020)
2010 – 2019
- 2019
- [j100]Jasper Tan, Li Niu, Jesse K. Adams, Vivek Boominathan, Jacob T. Robinson, Richard G. Baraniuk, Ashok Veeraraghavan:
Face Detection and Verification Using Lensless Cameras. IEEE Trans. Computational Imaging 5(2): 180-194 (2019) - [c187]Daniel LeJeune, Reinhard Heckel, Richard G. Baraniuk:
Adaptive Estimation for Approximate k-Nearest-Neighbor Computations. AISTATS 2019: 3099-3107 - [c186]Indu Manickam, Andrew S. Lan, Gautam Dasarathy, Richard G. Baraniuk:
IdeoTrace: a framework for ideology tracing with a case study on the 2016 U.S. presidential election. ASONAM 2019: 274-281 - [c185]Zichao Wang, Andrew S. Lan, Andrew E. Waters, Phillip Grimaldi, Richard G. Baraniuk:
A Meta-Learning Augmented Bidirectional Transformer Model for Automatic Short Answer Grading. EDM 2019 - [c184]Randall Balestriero, Richard G. Baraniuk:
From Hard to Soft: Understanding Deep Network Nonlinearities via Vector Quantization and Statistical Inference. ICLR (Poster) 2019 - [c183]Joshua J. Michalenko, Ameesh Shah, Abhinav Verma, Richard G. Baraniuk, Swarat Chaudhuri, Ankit B. Patel:
Representing Formal Languages: A Comparison Between Finite Automata and Recurrent Neural Networks. ICLR (Poster) 2019 - [c182]Ali Mousavi, Gautam Dasarathy, Richard G. Baraniuk:
A Data-Driven and Distributed Approach to Sparse Signal Representation and Recovery. ICLR (Poster) 2019 - [c181]Zichao Wang, Randall Balestriero, Richard G. Baraniuk:
A Max-Affine Spline Perspective of Recurrent Neural Networks. ICLR (Poster) 2019 - [c180]Randall Balestriero, Romain Cosentino, Behnaam Aazhang, Richard G. Baraniuk:
The Geometry of Deep Networks: Power Diagram Subdivision. NeurIPS 2019: 15806-15815 - [e1]Sergey A. Sosnovsky, Peter Brusilovsky, Richard G. Baraniuk, Rakesh Agrawal, Andrew S. Lan:
Proceedings of the First Workshop on Intelligent Textbooks co-located with 20th International Conference on Artificial Intelligence in Education (AIED 2019), Chicago, IL, USA, June 25, 2019. CEUR Workshop Proceedings 2384, CEUR-WS.org 2019 [contents] - [i84]Benjamin Coleman, Anshumali Shrivastava, Richard G. Baraniuk:
RACE: Sub-Linear Memory Sketches for Approximate Near-Neighbor Search on Streaming Data. CoRR abs/1902.06687 (2019) - [i83]Daniel LeJeune, Richard G. Baraniuk, Reinhard Heckel:
Adaptive Estimation for Approximate k-Nearest-Neighbor Computations. CoRR abs/1902.09465 (2019) - [i82]Joshua J. Michalenko, Ameesh Shah, Abhinav Verma, Richard G. Baraniuk, Swarat Chaudhuri, Ankit B. Patel:
Representing Formal Languages: A Comparison Between Finite Automata and Recurrent Neural Networks. CoRR abs/1902.10297 (2019) - [i81]Randall Balestriero, Romain Cosentino, Behnaam Aazhang, Richard G. Baraniuk:
The Geometry of Deep Networks: Power Diagram Subdivision. CoRR abs/1905.08443 (2019) - [i80]Indu Manickam, Andrew S. Lan, Gautam Dasarathy, Richard G. Baraniuk:
IdeoTrace: A Framework for Ideology Tracing with a Case Study on the 2016 U.S. Presidential Election. CoRR abs/1905.08831 (2019) - [i79]Daniel LeJeune, Gautam Dasarathy, Richard G. Baraniuk:
Thresholding Graph Bandits with GrAPL. CoRR abs/1905.09190 (2019) - [i78]Hamid Javadi, Randall Balestriero, Richard G. Baraniuk:
A Hessian Based Complexity Measure for Deep Networks. CoRR abs/1905.11639 (2019) - [i77]Yue Wang, Jianghao Shen, Ting-Kuei Hu, Pengfei Xu, Tan M. Nguyen, Richard G. Baraniuk, Zhangyang Wang, Yingyan Lin:
Dual Dynamic Inference: Enabling More Efficient, Adaptive and Controllable Deep Inference. CoRR abs/1907.04523 (2019) - [i76]Yujia Huang, Sihui Dai, Tan M. Nguyen, Richard G. Baraniuk, Anima Anandkumar:
Out-of-Distribution Detection Using Neural Rendering Generative Models. CoRR abs/1907.04572 (2019) - [i75]Haoran You, Chaojian Li, Pengfei Xu, Yonggan Fu, Yue Wang, Xiaohan Chen, Yingyan Lin, Zhangyang Wang, Richard G. Baraniuk:
Drawing early-bird tickets: Towards more efficient training of deep networks. CoRR abs/1909.11957 (2019) - [i74]Daniel LeJeune, Hamid Javadi, Richard G. Baraniuk:
The Implicit Regularization of Ordinary Least Squares Ensembles. CoRR abs/1910.04743 (2019) - [i73]Tan M. Nguyen, Animesh Garg, Richard G. Baraniuk, Anima Anandkumar:
InfoCNF: An Efficient Conditional Continuous Normalizing Flow with Adaptive Solvers. CoRR abs/1912.03978 (2019) - 2018
- [j99]Amirali Aghazadeh, Mohammad Golbabaee, Andrew S. Lan, Richard G. Baraniuk:
Insense: Incoherent sensor selection for sparse signals. Signal Process. 150: 57-65 (2018) - [j98]Azalia Mirhoseini, Eva L. Dyer, Ebrahim M. Songhori, Richard G. Baraniuk, Farinaz Koushanfar:
RankMap: A Framework for Distributed Learning From Dense Data Sets. IEEE Trans. Neural Networks Learn. Syst. 29(7): 2717-2730 (2018) - [c179]Nathan Dunkelberger, Jennifer L. Sullivan, Joshua Bradley, Nickolas P. Walling, Indu Manickam, Gautam Dasarathy, Ali Israr, Frances W. Y. Lau, Keith Klumb, Brian Knott, Freddy Abnousi, Richard G. Baraniuk, Marcia K. O'Malley:
Conveying language through haptics: a multi-sensory approach. UbiComp 2018: 25-32 - [c178]Christopher A. Metzler, Philip Schniter, Richard G. Baraniuk:
An Expectation-Maximization Approach to Tuning Generalized Vector Approximate Message Passing. LVA/ICA 2018: 395-406 - [c177]Amirali Aghazadeh, Mohammad Golbabaee, Andrew S. Lan, Richard G. Baraniuk:
Insense: Incoherent Sensor Selection for Sparse Signals. ICASSP 2018: 4689-4693 - [c176]Amirali Aghazadeh, Ryan Spring, Daniel LeJeune, Gautam Dasarathy, Anshumali Shrivastava, Richard G. Baraniuk:
MISSION: Ultra Large-Scale Feature Selection using Count-Sketches. ICML 2018: 80-88 - [c175]Randall Balestriero, Romain Cosentino, Hervé Glotin, Richard G. Baraniuk:
Spline Filters For End-to-End Deep Learning. ICML 2018: 373-382 - [c174]Randall Balestriero, Richard G. Baraniuk:
A Spline Theory of Deep Networks. ICML 2018: 383-392 - [c173]Christopher A. Metzler, Philip Schniter, Ashok Veeraraghavan, Richard G. Baraniuk:
prDeep: Robust Phase Retrieval with a Flexible Deep Network. ICML 2018: 3498-3507 - [c172]Zichao Wang, Andrew S. Lan, Weili Nie, Andrew E. Waters, Phillip J. Grimaldi, Richard G. Baraniuk:
QG-net: a data-driven question generation model for educational content. L@S 2018: 7:1-7:10 - [i72]Randall Balestriero, Hervé Glotin, Richard G. Baraniuk:
Semi-Supervised Learning Enabled by Multiscale Deep Neural Network Inversion. CoRR abs/1802.10172 (2018) - [i71]Christopher A. Metzler, Philip Schniter, Ashok Veeraraghavan, Richard G. Baraniuk:
prDeep: Robust Phase Retrieval with Flexible Deep Neural Networks. CoRR abs/1803.00212 (2018) - [i70]Randall Balestriero, Richard G. Baraniuk:
A Spline Theory of Deep Networks (Extended Version). CoRR abs/1805.06576 (2018) - [i69]Christopher A. Metzler, Ali Mousavi, Reinhard Heckel, Richard G. Baraniuk:
Unsupervised Learning with Stein's Unbiased Risk Estimator. CoRR abs/1805.10531 (2018) - [i68]Amirali Aghazadeh, Ryan Spring, Daniel LeJeune, Gautam Dasarathy, Anshumali Shrivastava, Richard G. Baraniuk:
MISSION: Ultra Large-Scale Feature Selection using Count-Sketches. CoRR abs/1806.04310 (2018) - [i67]Christopher A. Metzler, Philip Schniter, Richard G. Baraniuk:
An Expectation-Maximization Approach to Tuning Generalized Vector Approximate Message Passing. CoRR abs/1806.10079 (2018) - [i66]Randall Balestriero, Richard G. Baraniuk:
From Hard to Soft: Understanding Deep Network Nonlinearities via Vector Quantization and Statistical Inference. CoRR abs/1810.09274 (2018) - [i65]Nhat Ho, Tan M. Nguyen, Ankit B. Patel, Anima Anandkumar, Michael I. Jordan, Richard G. Baraniuk:
Neural Rendering Model: Joint Generation and Prediction for Semi-Supervised Learning. CoRR abs/1811.02657 (2018) - 2017
- [j97]Mihaela van der Schaar, Richard G. Baraniuk, Mung Chiang, Jonathan Huang, Shengdong Zhao:
Introduction to the Issue on Signal Processing and Machine Learning. IEEE J. Sel. Top. Signal Process. 11(5): 713-715 (2017) - [j96]Andrew S. Lan, Andrew E. Waters, Christoph Studer, Richard G. Baraniuk:
BLAh: Boolean Logic Analysis for Graded Student Response Data. IEEE J. Sel. Top. Signal Process. 11(5): 754-764 (2017) - [j95]Richard G. Baraniuk, Thomas A. Goldstein, Aswin C. Sankaranarayanan, Christoph Studer, Ashok Veeraraghavan, Michael B. Wakin:
Compressive Video Sensing: Algorithms, architectures, and applications. IEEE Signal Process. Mag. 34(1): 52-66 (2017) - [j94]M. Salman Asif, Ali Ayremlou, Aswin C. Sankaranarayanan, Ashok Veeraraghavan, Richard G. Baraniuk:
FlatCam: Thin, Lensless Cameras Using Coded Aperture and Computation. IEEE Trans. Computational Imaging 3(3): 384-397 (2017) - [j93]Richard G. Baraniuk, Simon Foucart, Deanna Needell, Yaniv Plan, Mary Wootters:
Exponential Decay of Reconstruction Error From Binary Measurements of Sparse Signals. IEEE Trans. Inf. Theory 63(6): 3368-3385 (2017) - [c171]Gautam Dasarathy, Parikshit Shah, Richard G. Baraniuk:
Sketched covariance testing: A compression-statistics tradeoff. ACSSC 2017: 676-680 - [c170]Ali Mousavi, Gautam Dasarathy, Richard G. Baraniuk:
DeepCodec: Adaptive sensing and recovery via deep convolutional neural networks. Allerton 2017: 744 - [c169]Joshua J. Michalenko, Andrew S. Lan, Richard G. Baraniuk:
Personalized Feedback for Open-Response Mathematical Questions using Long Short-Term Memory Networks. EDM 2017 - [c168]Joshua J. Michalenko, Andrew S. Lan, Andrew E. Waters, Phillip Grimaldi, Richard G. Baraniuk:
Data-Mining Textual Responses to Uncover Misconception Patterns. EDM 2017 - [c167]Jack Z. Wang, Andrew S. Lan, Phillip Grimaldi, Richard G. Baraniuk:
A Latent Factor Model For Instructor Content Preference Analysis. EDM 2017 - [c166]Andrew E. Waters, Phillip Grimaldi, Andrew S. Lan, Richard G. Baraniuk:
Short-Answer Responses to STEM Exercises: Measuring Response Validity and Its Impact on Learning. EDM 2017 - [c165]Ali Mousavi, Richard G. Baraniuk:
Learning to invert: Signal recovery via Deep Convolutional Networks. ICASSP 2017: 2272-2276 - [c164]Indu Manickam, Andrew S. Lan, Richard G. Baraniuk:
Contextual multi-armed bandit algorithms for personalized learning action selection. ICASSP 2017: 6344-6348 - [c163]Jasper Tan, Vivek Boominathan, Ashok Veeraraghavan, Richard G. Baraniuk:
Flat focus: depth of field analysis for the FlatCam lensless imaging system. ICASSP 2017: 6473-6477 - [c162]Christopher A. Metzler, Manoj Kumar Sharma, Sudarshan Nagesh, Richard G. Baraniuk, Oliver Cossairt, Ashok Veeraraghavan:
Coherent inverse scattering via transmission matrices: Efficient phase retrieval algorithms and a public dataset. ICCP 2017: 51-66 - [c161]Amirali Aghazadeh, Andrew S. Lan, Anshumali Shrivastava, Richard G. Baraniuk:
RHash: Robust Hashing via L_infinity-norm Distortion. IJCAI 2017: 1386-1394 - [c160]Gautam Dasarathy, Parikshit Shah, Richard G. Baraniuk:
Sketched covariance testing: A compression-statistics tradeoff. ISIT 2017: 2268-2272 - [c159]Joshua J. Michalenko, Andrew S. Lan, Richard G. Baraniuk:
D.TRUMP: Data-mining Textual Responses to Uncover Misconception Patterns. L@S 2017: 245-248 - [c158]Christopher A. Metzler, Ali Mousavi, Richard G. Baraniuk:
Learned D-AMP: Principled Neural Network based Compressive Image Recovery. NIPS 2017: 1772-1783 - [i64]Ali Mousavi, Richard G. Baraniuk:
Learning to Invert: Signal Recovery via Deep Convolutional Networks. CoRR abs/1701.03891 (2017) - [i63]Amirali Aghazadeh, Mohammad Golbabaee, Andrew S. Lan, Richard G. Baraniuk:
Insense: Incoherent Sensor Selection for Sparse Signals. CoRR abs/1702.07670 (2017) - [i62]Joshua J. Michalenko, Andrew S. Lan, Richard G. Baraniuk:
Data-Mining Textual Responses to Uncover Misconception Patterns. CoRR abs/1703.08544 (2017) - [i61]Christopher A. Metzler, Ali Mousavi, Richard G. Baraniuk:
Learned D-AMP: A Principled CNN-based Compressive Image Recovery Algorithm. CoRR abs/1704.06625 (2017) - [i60]Ali Mousavi, Gautam Dasarathy, Richard G. Baraniuk:
DeepCodec: Adaptive Sensing and Recovery via Deep Convolutional Neural Networks. CoRR abs/1707.03386 (2017) - [i59]Randall Balestriero, Richard G. Baraniuk:
Adaptive Partitioning Spline Neural Networks: Template Matching, Memorization, Inhibitor Connections, Inversion, Semi-Sup, Topology Search. CoRR abs/1710.09302 (2017) - [i58]Randall Balestriero, Vincent Roger, Hervé Glotin, Richard G. Baraniuk:
Semi-Supervised Learning via New Deep Network Inversion. CoRR abs/1711.04313 (2017) - [i57]Romain Cosentino, Randall Balestriero, Richard G. Baraniuk, Ankit B. Patel:
Overcomplete Frame Thresholding for Acoustic Scene Analysis. CoRR abs/1712.09117 (2017) - 2016
- [j92]Thomas A. Baran, Richard G. Baraniuk, Alan V. Oppenheim, Paolo Prandoni, Martin Vetterli:
MOOC Adventures in Signal Processing: Bringing DSP to the era of massive open online courses. IEEE Signal Process. Mag. 33(4): 62-83 (2016) - [j91]Amit K. Agrawal, Richard G. Baraniuk, Pablo Favaro, Ashok Veeraraghavan:
Signal Processing for Computational Photography and Displays [From the Guest Editors]. IEEE Signal Process. Mag. 33(5): 12-15 (2016) - [j90]Vivek Boominathan, Jesse K. Adams, M. Salman Asif, Benjamin W. Avants, Jacob T. Robinson, Richard G. Baraniuk, Aswin C. Sankaranarayanan, Ashok Veeraraghavan:
Lensless Imaging: A computational renaissance. IEEE Signal Process. Mag. 33(5): 23-35 (2016) - [j89]Christopher A. Metzler, Arian Maleki, Richard G. Baraniuk:
From Denoising to Compressed Sensing. IEEE Trans. Inf. Theory 62(9): 5117-5144 (2016) - [c157]Divyanshu Vats, Andrew S. Lan, Christoph Studer, Richard G. Baraniuk:
Optimal ranking of test items using the Rasch model. Allerton 2016: 467-473 - [c156]Andrew S. Lan, Richard G. Baraniuk:
A Contextual Bandits Framework for Personalized Learning Action Selection. EDM 2016: 424-429 - [c155]Christopher A. Metzler, Arian Maleki, Richard G. Baraniuk:
BM3D-PRGAMP: Compressive phase retrieval based on BM3D denoising. ICIP 2016: 2504-2508 - [c154]Christopher A. Metzler, Arian Maleki, Richard G. Baraniuk:
BM3D-PRGAMP: Compressive phase retrieval based on BM3D denoising. ICME Workshops 2016: 1-2 - [c153]Andrew S. Lan, Tom Goldstein, Richard G. Baraniuk, Christoph Studer:
Dealbreaker: A Nonlinear Latent Variable Model for Educational Data. ICML 2016: 266-275 - [c152]Ankit B. Patel, Minh Tan Nguyen, Richard G. Baraniuk:
A Probabilistic Framework for Deep Learning. NIPS 2016: 2550-2558 - [c151]Raajen Patel, Tom Goldstein, Eva L. Dyer, Azalia Mirhoseini, Richard G. Baraniuk:
Deterministic Column Sampling for Low-Rank Matrix Approximation: Nyström vs. Incomplete Cholesky Decomposition. SDM 2016: 594-602 - [i56]Amirali Aghazadeh, Andrew S. Lan, Anshumali Shrivastava, Richard G. Baraniuk:
Near-Isometric Binary Hashing for Large-scale Datasets. CoRR abs/1603.03836 (2016) - [i55]Richard G. Baraniuk, Simon Foucart, Deanna Needell, Yaniv Plan, Mary Wootters:
One-Bit Compressive Sensing of Dictionary-Sparse Signals. CoRR abs/1606.07531 (2016) - [i54]Ankit B. Patel, Minh Tan Nguyen, Richard G. Baraniuk:
A Probabilistic Framework for Deep Learning. CoRR abs/1612.01936 (2016) - [i53]Minh Tan Nguyen, Wanjia Liu, Ethan Perez, Richard G. Baraniuk, Ankit B. Patel:
Semi-Supervised Learning with the Deep Rendering Mixture Model. CoRR abs/1612.01942 (2016) - 2015
- [j88]Aswin C. Sankaranarayanan, Lina Xu, Christoph Studer, Yun Li, Kevin F. Kelly, Richard G. Baraniuk:
Video Compressive Sensing for Spatial Multiplexing Cameras Using Motion-Flow Models. SIAM J. Imaging Sci. 8(3): 1489-1518 (2015) - [j87]Tom Goldstein, Lina Xu, Kevin F. Kelly, Richard G. Baraniuk:
The STOne Transform: Multi-Resolution Image Enhancement and Compressive Video. IEEE Trans. Image Process. 24(12): 5581-5593 (2015) - [j86]Chinmay Hegde, Aswin C. Sankaranarayanan, Wotao Yin, Richard G. Baraniuk:
NuMax: A Convex Approach for Learning Near-Isometric Linear Embeddings. IEEE Trans. Signal Process. 63(22): 6109-6121 (2015) - [c150]Sally L. Wood, Ernesto Fontenla, Christopher A. Metzler, Wah Chiu, Richard G. Baraniuk:
Iterative reconstruction from limited angle, limited view projections for cryo-electron tomography. ACSSC 2015: 760-764 - [c149]Ali Mousavi, Richard G. Baraniuk:
An information-theoretic measure of dependency among variables in large datasets. Allerton 2015: 650-657 - [c148]Ali Mousavi, Ankit B. Patel, Richard G. Baraniuk:
A deep learning approach to structured signal recovery. Allerton 2015: 1336-1343 - [c147]Sally L. Wood, Ernesto Fontenla, Christopher A. Metzler, Wah Chiu, Richard G. Baraniuk:
Dynamic model generation for application of compressed sensing to cryo-electron tomography reconstruction. SP/SPE 2015: 226-231 - [c146]M. Salman Asif, Ali Ayremlou, Ashok Veeraraghavan, Richard G. Baraniuk, Aswin C. Sankaranarayanan:
FlatCam: Replacing Lenses with Masks and Computation. ICCV Workshops 2015: 663-666 - [c145]Christopher A. Metzler, Arian Maleki, Richard G. Baraniuk:
BM3D-AMP: A new image recovery algorithm based on BM3D denoising. ICIP 2015: 3116-3120 - [c144]Andrew S. Lan, Divyanshu Vats, Andrew E. Waters, Richard G. Baraniuk:
Mathematical Language Processing: Automatic Grading and Feedback for Open Response Mathematical Questions. L@S 2015: 167-176 - [c143]Andrew E. Waters, David Tinapple, Richard G. Baraniuk:
BayesRank: A Bayesian Approach to Ranked Peer Grading. L@S 2015: 177-183 - [i52]Andrew S. Lan, Divyanshu Vats, Andrew E. Waters, Richard G. Baraniuk:
Mathematical Language Processing: Automatic Grading and Feedback for Open Response Mathematical Questions. CoRR abs/1501.04346 (2015) - [i51]Tom Goldstein, Christoph Studer, Richard G. Baraniuk:
FASTA: A Generalized Implementation of Forward-Backward Splitting. CoRR abs/1501.04979 (2015) - [i50]Aswin C. Sankaranarayanan, Lina Xu, Christoph Studer, Yun Li, Kevin F. Kelly, Richard G. Baraniuk:
Video Compressive Sensing for Spatial Multiplexing Cameras using Motion-Flow Models. CoRR abs/1503.02727 (2015) - [i49]Azalia Mirhoseini, Eva L. Dyer, Ebrahim M. Songhori, Richard G. Baraniuk, Farinaz Koushanfar:
RankMap: A Platform-Aware Framework for Distributed Learning from Dense Datasets. CoRR abs/1503.08169 (2015) - [i48]Ankit B. Patel, Minh Tan Nguyen, Richard G. Baraniuk:
A Probabilistic Theory of Deep Learning. CoRR abs/1504.00641 (2015) - [i47]Eva L. Dyer, Tom Goldstein, Raajen Patel, Konrad P. Körding, Richard G. Baraniuk:
Self-Expressive Decompositions for Matrix Approximation and Clustering. CoRR abs/1505.00824 (2015) - [i46]Raajen Patel, Thomas A. Goldstein, Eva L. Dyer, Azalia Mirhoseini, Richard G. Baraniuk:
oASIS: Adaptive Column Sampling for Kernel Matrix Approximation. CoRR abs/1505.05208 (2015) - [i45]Ali Mousavi, Ankit B. Patel, Richard G. Baraniuk:
A Deep Learning Approach to Structured Signal Recovery. CoRR abs/1508.04065 (2015) - [i44]Ali Mousavi, Richard G. Baraniuk:
An Information-Theoretic Measure of Dependency Among Variables in Large Datasets. CoRR abs/1508.04073 (2015) - [i43]M. Salman Asif, Ali Ayremlou, Aswin C. Sankaranarayanan, Ashok Veeraraghavan, Richard G. Baraniuk:
FlatCam: Thin, Bare-Sensor Cameras using Coded Aperture and Computation. CoRR abs/1509.00116 (2015) - [i42]Ali Mousavi, Arian Maleki, Richard G. Baraniuk:
Consistent Parameter Estimation for LASSO and Approximate Message Passing. CoRR abs/1511.01017 (2015) - 2014
- [j85]Kaushik Mitra, Ashok Veeraraghavan, Aswin C. Sankaranarayanan, Richard G. Baraniuk:
Toward Compressive Camera Networks. Computer 47(5): 52-59 (2014) - [j84]Andrew S. Lan, Andrew E. Waters, Christoph Studer, Richard G. Baraniuk:
Sparse factor analysis for learning and content analytics. J. Mach. Learn. Res. 15(1): 1959-2008 (2014) - [j83]Tom Goldstein, Brendan O'Donoghue, Simon Setzer, Richard G. Baraniuk:
Fast Alternating Direction Optimization Methods. SIAM J. Imaging Sci. 7(3): 1588-1623 (2014) - [j82]Rebecca M. Willett, Marco F. Duarte, Mark A. Davenport, Richard G. Baraniuk:
Sparsity and Structure in Hyperspectral Imaging : Sensing, Reconstruction, and Target Detection. IEEE Signal Process. Mag. 31(1): 116-126 (2014) - [j81]Shirin Jalali, Arian Maleki, Richard G. Baraniuk:
Minimum Complexity Pursuit for Universal Compressed Sensing. IEEE Trans. Inf. Theory 60(4): 2253-2268 (2014) - [c142]Divyanshu Vats, Richard G. Baraniuk:
Path Thresholding: Asymptotically Tuning-Free High-Dimensional Sparse Regression. AISTATS 2014: 948-957 - [c141]Divyanshu Vats, Robert D. Nowak, Richard G. Baraniuk:
Active Learning for Undirected Graphical Model Selection. AISTATS 2014: 958-967 - [c140]Andrew S. Lan, Christoph Studer, Richard G. Baraniuk:
Quantized Matrix Completion for Personalized Learning. EDM 2014: 280-283 - [c139]Chinmay Hegde, Aswin C. Sankaranarayanan, Richard G. Baraniuk:
LIE operators for compressive sensing. ICASSP 2014: 2342-2346 - [c138]Andrew S. Lan, Christoph Studer, Richard G. Baraniuk:
Matrix recovery from quantized and corrupted measurements. ICASSP 2014: 4973-4977 - [c137]Andrew S. Lan, Christoph Studer, Richard G. Baraniuk:
Time-varying learning and content analytics via sparse factor analysis. KDD 2014: 452-461 - [r1]Aswin C. Sankaranarayanan, Richard G. Baraniuk:
Compressive Sensing. Computer Vision, A Reference Guide 2014: 132-136 - [i41]Christoph Studer, Tom Goldstein, Wotao Yin, Richard G. Baraniuk:
Democratic Representations. CoRR abs/1401.3420 (2014) - [i40]Jianing Shi, Wotao Yin, Aswin C. Sankaranarayanan, Richard G. Baraniuk:
Video Compressive Sensing for Dynamic MRI. CoRR abs/1401.7715 (2014) - [i39]Divyanshu Vats, Richard G. Baraniuk:
Path Thresholding: Asymptotically Tuning-Free High-Dimensional Sparse Regression. CoRR abs/1402.5584 (2014) - [i38]Divyanshu Vats, Robert D. Nowak, Richard G. Baraniuk:
Active Learning for Undirected Graphical Model Selection. CoRR abs/1404.3418 (2014) - [i37]Jianing Shi, Yangyang Xu, Richard G. Baraniuk:
Sparse Bilinear Logistic Regression. CoRR abs/1404.4104 (2014) - [i36]Christopher A. Metzler, Arian Maleki, Richard G. Baraniuk:
From Denoising to Compressed Sensing. CoRR abs/1406.4175 (2014) - [i35]Richard G. Baraniuk, Simon Foucart, Deanna Needell, Yaniv Plan, Mary Wootters:
Exponential decay of reconstruction error from binary measurements of sparse signals. CoRR abs/1407.8246 (2014) - [i34]Tom Goldstein, Christoph Studer, Richard G. Baraniuk:
A Field Guide to Forward-Backward Splitting with a FASTA Implementation. CoRR abs/1411.3406 (2014) - [i33]Ali Ayremlou, Thomas A. Goldstein, Ashok Veeraraghavan, Richard G. Baraniuk:
Fast Sublinear Sparse Representation using Shallow Tree Matching Pursuit. CoRR abs/1412.0680 (2014) - [i32]Andrew S. Lan, Christoph Studer, Andrew E. Waters, Richard G. Baraniuk:
Tag-Aware Ordinal Sparse Factor Analysis for Learning and Content Analytics. CoRR abs/1412.5967 (2014) - [i31]Andrew S. Lan, Christoph Studer, Richard G. Baraniuk:
Quantized Matrix Completion for Personalized Learning. CoRR abs/1412.5968 (2014) - 2013
- [j80]Eva L. Dyer, Aswin C. Sankaranarayanan, Richard G. Baraniuk:
Greedy feature selection for subspace clustering. J. Mach. Learn. Res. 14(1): 2487-2517 (2013) - [j79]Aswin C. Sankaranarayanan, Pavan K. Turaga, Rama Chellappa, Richard G. Baraniuk:
Compressive Acquisition of Linear Dynamical Systems. SIAM J. Imaging Sci. 6(4): 2109-2133 (2013) - [j78]Laurent Jacques, Jason N. Laska, Petros T. Boufounos, Richard G. Baraniuk:
Robust 1-Bit Compressive Sensing via Binary Stable Embeddings of Sparse Vectors. IEEE Trans. Inf. Theory 59(4): 2082-2102 (2013) - [j77]Marco F. Duarte, Michael B. Wakin, Dror Baron, Shriram Sarvotham, Richard G. Baraniuk:
Measurement Bounds for Sparse Signal Ensembles via Graphical Models. IEEE Trans. Inf. Theory 59(7): 4280-4289 (2013) - [j76]Arian Maleki, Laura Anitori, Zai Yang, Richard G. Baraniuk:
Asymptotic Analysis of Complex LASSO via Complex Approximate Message Passing (CAMP). IEEE Trans. Inf. Theory 59(7): 4290-4308 (2013) - [j75]Laura Anitori, Arian Maleki, Matern Otten, Richard G. Baraniuk, Peter Hoogeboom:
Design and Analysis of Compressed Sensing Radar Detectors. IEEE Trans. Signal Process. 61(4): 813-827 (2013) - [c136]Andrew S. Lan, Christoph Studer, Andrew E. Waters, Richard G. Baraniuk:
Tag-Aware Ordinal Sparse Factor Analysis for Learning and Content Analytics. EDM 2013: 90-97 - [c135]Divyanshu Vats, Christoph Studer, Andrew S. Lan, Lawrence Carin, Richard G. Baraniuk:
Test-size Reduction for Concept Estimation. EDM 2013: 292-295 - [c134]Andrew S. Lan, Christoph Studer, Andrew E. Waters, Richard G. Baraniuk:
Joint Topic Modeling and Factor Analysis of Textual Information and Graded Response Data. EDM 2013: 324-325 - [c133]Laura Anitori, Wim Van Rossum, Matern Otten, Arian Maleki, Richard G. Baraniuk:
Compressive sensing radar: Simulation and experiments for target detection. EUSIPCO 2013: 1-5 - [c132]Andrew E. Waters, Christoph Studer, Richard G. Baraniuk:
Bayesian pairwise collaboration detection in educational datasets. GlobalSIP 2013: 989-992 - [c131]Eva L. Dyer, Christoph Studer, Richard G. Baraniuk:
Subspace clustering with dense representations. ICASSP 2013: 3258-3262 - [c130]Amirali Aghazadeh, Ali Ayremlou, Daniel D. Calderon, Tom Goldstein, Raajen Patel, Divyanshu Vats, Richard G. Baraniuk:
Adaptive step size selection for optimization via the ski rental problem. ICASSP 2013: 5383-5387 - [c129]John P. Slavinsky, Kim J. Davenport, Andrew C. Butler, Elizabeth J. Marsh, Richard G. Baraniuk:
Open online platforms advancing DSP education. ICASSP 2013: 8771-8775 - [c128]Divyanshu Vats, Richard G. Baraniuk:
When in Doubt, SWAP: High-Dimensional Sparse Recovery from Correlated Measurements. NIPS 2013: 989-997 - [i30]Armeen Taeb, Arian Maleki, Christoph Studer, Richard G. Baraniuk:
Maximin Analysis of Message Passing Algorithms for Recovering Block Sparse Signals. CoRR abs/1303.2389 (2013) - [i29]Eva L. Dyer, Aswin C. Sankaranarayanan, Richard G. Baraniuk:
Greedy Feature Selection for Subspace Clustering. CoRR abs/1303.4778 (2013) - [i28]Andrew S. Lan, Andrew E. Waters, Christoph Studer, Richard G. Baraniuk:
Sparse Factor Analysis for Learning and Content Analytics. CoRR abs/1303.5685 (2013) - [i27]Andrew S. Lan, Christoph Studer, Andrew E. Waters, Richard G. Baraniuk:
Joint Topic Modeling and Factor Analysis of Textual Information and Graded Response Data. CoRR abs/1305.1956 (2013) - [i26]Ali Mousavi, Arian Maleki, Richard G. Baraniuk:
Asymptotic Analysis of LASSOs Solution Path with Implications for Approximate Message Passing. CoRR abs/1309.5979 (2013) - [i25]Ali Mousavi, Arian Maleki, Richard G. Baraniuk:
Parameterless Optimal Approximate Message Passing. CoRR abs/1311.0035 (2013) - [i24]Tom Goldstein, Lina Xu, Kevin F. Kelly, Richard G. Baraniuk:
The STONE Transform: Multi-Resolution Image Enhancement and Real-Time Compressive Video. CoRR abs/1311.3405 (2013) - [i23]Divyanshu Vats, Richard G. Baraniuk:
Swapping Variables for High-Dimensional Sparse Regression from Correlated Measurements. CoRR abs/1312.1706 (2013) - [i22]Andrew S. Lan, Christoph Studer, Richard G. Baraniuk:
Time-varying Learning and Content Analytics via Sparse Factor Analysis. CoRR abs/1312.5734 (2013) - 2012
- [j74]Patrick Maechler, Christoph Studer, David E. Bellasi, Arian Maleki, Andreas Burg, Norbert Felber, Hubert Kaeslin, Richard G. Baraniuk:
VLSI Design of Approximate Message Passing for Signal Restoration and Compressive Sensing. IEEE J. Emerg. Sel. Topics Circuits Syst. 2(3): 579-590 (2012) - [j73]Richard G. Baraniuk, Wayne T. Padgett:
Trends in Signal Processing Education [In the Spotlight]. IEEE Signal Process. Mag. 29(1): 180-182 (2012) - [j72]Marco F. Duarte, Richard G. Baraniuk:
Kronecker Compressive Sensing. IEEE Trans. Image Process. 21(2): 494-504 (2012) - [j71]Chinmay Hegde, Richard G. Baraniuk:
Signal Recovery on Incoherent Manifolds. IEEE Trans. Inf. Theory 58(12): 7204-7214 (2012) - [j70]Jason N. Laska, Richard G. Baraniuk:
Regime Change: Bit-Depth Versus Measurement-Rate in Compressive Sensing. IEEE Trans. Signal Process. 60(7): 3496-3505 (2012) - [j69]Mark A. Davenport, Jason N. Laska, John R. Treichler, Richard G. Baraniuk:
The Pros and Cons of Compressive Sensing for Wideband Signal Acquisition: Noise Folding versus Dynamic Range. IEEE Trans. Signal Process. 60(9): 4628-4642 (2012) - [c127]Christoph Studer, Wotao Yin, Richard G. Baraniuk:
Signal representations with minimum ℓ∞-norm. Allerton Conference 2012: 1270-1277 - [c126]Stephen R. Schnelle, John P. Slavinsky, Petros Boufounos, Mark A. Davenport, Richard G. Baraniuk:
A compressive phase-locked loop. ICASSP 2012: 2885-2888 - [c125]Christoph Studer, Richard G. Baraniuk:
Dictionary learning from sparsely corrupted or compressed signals. ICASSP 2012: 3341-3344 - [c124]Andrew E. Waters, Charles K. Sestok, Richard G. Baraniuk:
A bit-constrained sar adc for compressive acquisition of frequency sparse signals. ICASSP 2012: 5313-5316 - [c123]Aswin C. Sankaranarayanan, Christoph Studer, Richard G. Baraniuk:
CS-MUVI: Video compressive sensing for spatial-multiplexing cameras. ICCP 2012: 1-10 - [c122]Chinmay Hegde, Richard G. Baraniuk:
SPIN: Iterative signal recovery on incoherent manifolds. ISIT 2012: 1296-1300 - [c121]Shirin Jalali, Arian Maleki, Richard G. Baraniuk:
Minimum complexity pursuit: Stability analysis. ISIT 2012: 1857-1861 - [c120]Jarvis D. Haupt, Richard G. Baraniuk, Rui M. Castro, Robert D. Nowak:
Sequentially designed compressed sensing. SSP 2012: 401-404 - [c119]Chinmay Hegde, Aswin C. Sankaranarayanan, Richard G. Baraniuk:
Near-isometric linear embeddings of manifolds. SSP 2012: 728-731 - [c118]Devin K. Grady, Mark Moll, Chinmay Hegde, Aswin C. Sankaranarayanan, Richard G. Baraniuk, Lydia E. Kavraki:
Multi-objective sensor-based replanning for a car-like robot. SSRR 2012: 1-6 - [c117]Devin K. Grady, Mark Moll, Chinmay Hegde, Aswin C. Sankaranarayanan, Richard G. Baraniuk, Lydia E. Kavraki:
Multi-robot target verification with reachability constraints. SSRR 2012: 1-6 - [i21]Aswin C. Sankaranarayanan, Pavan K. Turaga, Rama Chellappa, Richard G. Baraniuk:
Compressive Acquisition of Dynamic Scenes. CoRR abs/1201.4895 (2012) - [i20]Chinmay Hegde, Richard G. Baraniuk:
Signal Recovery on Incoherent Manifolds. CoRR abs/1202.1595 (2012) - [i19]Shirin Jalali, Arian Maleki, Richard G. Baraniuk:
Minimum Complexity Pursuit: Stability Analysis. CoRR abs/1205.4673 (2012) - [i18]Shirin Jalali, Arian Maleki, Richard G. Baraniuk:
Minimum Complexity Pursuit for Universal Compressed Sensing. CoRR abs/1208.5814 (2012) - 2011
- [j68]Lawrence Carin, Richard G. Baraniuk, Volkan Cevher, David B. Dunson, Michael I. Jordan, Guillermo Sapiro, Michael B. Wakin:
Learning Low-Dimensional Signal Models. IEEE Signal Process. Mag. 28(2): 39-51 (2011) - [j67]Chinmay Hegde, Richard G. Baraniuk:
Sampling and Recovery of Pulse Streams. IEEE Trans. Signal Process. 59(4): 1505-1517 (2011) - [j66]Jason N. Laska, Zaiwen Wen, Wotao Yin, Richard G. Baraniuk:
Trust, But Verify: Fast and Accurate Signal Recovery From 1-Bit Compressive Measurements. IEEE Trans. Signal Process. 59(11): 5289-5301 (2011) - [c116]Jason N. Laska, John P. Slavinsky, Richard G. Baraniuk:
The polyphase random demodulator for wideband compressive sensing. ACSCC 2011: 515-519 - [c115]Arian Maleki, Manjari Narayan, Richard G. Baraniuk:
Suboptimality of nonlocal means on images with sharp edges. Allerton 2011: 299-305 - [c114]Christoph Studer, Richard G. Baraniuk:
Recovery guarantees for restoration and separation of approximately sparse signals. Allerton 2011: 736-743 - [c113]Aswin C. Sankaranarayanan, Chinmay Hegde, Sriram Nagaraj, Richard G. Baraniuk:
Go with the flow: Optical flow-based transport operators for image manifolds. Allerton 2011: 1824-1831 - [c112]Jarvis D. Haupt, Richard G. Baraniuk:
Robust support recovery using sparse compressive sensing matrices. CISS 2011: 1-6 - [c111]John P. Slavinsky, Jason N. Laska, Mark A. Davenport, Richard G. Baraniuk:
The compressive multiplexer for multi-channel compressive sensing. ICASSP 2011: 3980-3983 - [c110]Arian Maleki, Richard G. Baraniuk:
Least favorable compressed sensing problems for first-order methods. ISIT 2011: 134-138 - [c109]Andrew E. Waters, Aswin C. Sankaranarayanan, Richard G. Baraniuk:
SpaRCS: Recovering low-rank and sparse matrices from compressive measurements. NIPS 2011: 1089-1097 - [i17]Marco F. Duarte, Michael B. Wakin, Dror Baron, Shriram Sarvotham, Richard G. Baraniuk:
Bounds on the Reconstruction of Sparse Signal Ensembles from Distributed Measurements. CoRR abs/1102.2677 (2011) - [i16]Shriram Sarvotham, Richard G. Baraniuk:
Deterministic Bounds for Restricted Isometry of Compressed Sensing Matrices. CoRR abs/1103.3316 (2011) - [i15]Laurent Jacques, Jason N. Laska, Petros Boufounos, Richard G. Baraniuk:
Robust 1-Bit Compressive Sensing via Binary Stable Embeddings of Sparse Vectors. CoRR abs/1104.3160 (2011) - [i14]Mark A. Davenport, Jason N. Laska, John R. Treichler, Richard G. Baraniuk:
The Pros and Cons of Compressive Sensing for Wideband Signal Acquisition: Noise Folding vs. Dynamic Range. CoRR abs/1104.4842 (2011) - [i13]Christoph Studer, Richard G. Baraniuk:
Stable Restoration and Separation of Approximately Sparse Signals. CoRR abs/1107.0420 (2011) - [i12]Arian Maleki, Laura Anitori, Zai Yang, Richard G. Baraniuk:
Asymptotic Analysis of Complex LASSO via Complex Approximate Message Passing (CAMP). CoRR abs/1108.0477 (2011) - [i11]Jason N. Laska, Richard G. Baraniuk:
Regime Change: Bit-Depth versus Measurement-Rate in Compressive Sensing. CoRR abs/1110.3450 (2011) - [i10]Sriram Nagaraj, Aswin C. Sankaranarayanan, Richard G. Baraniuk:
A Theory for Optical flow-based Transport on Image Manifolds. CoRR abs/1111.5108 (2011) - [i9]Arian Maleki, Manjari Narayan, Richard G. Baraniuk:
Suboptimality of Nonlocal Means for Images with Sharp Edges. CoRR abs/1111.5867 (2011) - [i8]Arian Maleki, Manjari Narayan, Richard G. Baraniuk:
Anisotropic Nonlocal Means Denoising. CoRR abs/1112.0311 (2011) - 2010
- [j65]Rick Chartrand, Richard G. Baraniuk, Yonina C. Eldar, Mário A. T. Figueiredo, Jared Tanner:
Introduction to the Issue on Compressive Sensing. IEEE J. Sel. Top. Signal Process. 4(2): 241-243 (2010) - [j64]Mark A. Davenport, Petros Boufounos, Michael B. Wakin, Richard G. Baraniuk:
Signal Processing With Compressive Measurements. IEEE J. Sel. Top. Signal Process. 4(2): 445-460 (2010) - [j63]Mark A. Davenport, Richard G. Baraniuk, Clayton D. Scott:
Tuning Support Vector Machines for Minimax and Neyman-Pearson Classification. IEEE Trans. Pattern Anal. Mach. Intell. 32(10): 1888-1898 (2010) - [j62]Richard G. Baraniuk, Emmanuel J. Candès, Michael Elad, Yi Ma:
Applications of Sparse Representation and Compressive Sensing. Proc. IEEE 98(6): 906-909 (2010) - [j61]Richard G. Baraniuk, Volkan Cevher, Michael B. Wakin:
Low-Dimensional Models for Dimensionality Reduction and Signal Recovery: A Geometric Perspective. Proc. IEEE 98(6): 959-971 (2010) - [j60]Volkan Cevher, Piotr Indyk, Lawrence Carin, Richard G. Baraniuk:
Sparse Signal Recovery and Acquisition with Graphical Models. IEEE Signal Process. Mag. 27(6): 92-103 (2010) - [j59]Mark A. Davenport, Chinmay Hegde, Marco F. Duarte, Richard G. Baraniuk:
Joint Manifolds for Data Fusion. IEEE Trans. Image Process. 19(10): 2580-2594 (2010) - [j58]Joel A. Tropp, Jason N. Laska, Marco F. Duarte, Justin K. Romberg, Richard G. Baraniuk:
Beyond Nyquist: efficient sampling of sparse bandlimited signals. IEEE Trans. Inf. Theory 56(1): 520-544 (2010) - [j57]Richard G. Baraniuk, Volkan Cevher, Marco F. Duarte, Chinmay Hegde:
Model-based compressive sensing. IEEE Trans. Inf. Theory 56(4): 1982-2001 (2010) - [j56]Dror Baron, Shriram Sarvotham, Richard G. Baraniuk:
Bayesian compressive sensing via belief propagation. IEEE Trans. Signal Process. 58(1): 269-280 (2010) - [c108]Mark A. Davenport, Chinmay Hegde, Marco F. Duarte, Richard G. Baraniuk:
High Dimensional Data Fusion via Joint Manifold Learning. AAAI Fall Symposium: Manifold Learning and Its Applications 2010 - [c107]Marco F. Duarte, Richard G. Baraniuk:
Recovery of frequency-sparse signals from compressive measurements. Allerton 2010: 599-606 - [c106]Aswin C. Sankaranarayanan, Pavan K. Turaga, Richard G. Baraniuk, Rama Chellappa:
Compressive Acquisition of Dynamic Scenes. ECCV (1) 2010: 129-142 - [c105]Eva L. Dyer, Marco F. Duarte, Don H. Johnson, Richard G. Baraniuk:
Recovering Spikes from Noisy Neuronal Calcium Signals via Structured Sparse Approximation. LVA/ICA 2010: 604-611 - [c104]Stephen R. Schnelle, Jason N. Laska, Chinmay Hegde, Marco F. Duarte, Mark A. Davenport, Richard G. Baraniuk:
Texas Hold 'Em algorithms for distributed compressive sensing. ICASSP 2010: 2886-2889 - [c103]Marco F. Duarte, Richard G. Baraniuk:
Kronecker product matrices for compressive sensing. ICASSP 2010: 3650-3653 - [c102]Chinmay Hegde, Richard G. Baraniuk:
Compressive sensing of a superposition of pulses. ICASSP 2010: 3934-3937 - [i7]Chinmay Hegde, Richard G. Baraniuk:
Sampling and Recovery of Pulse Streams. CoRR abs/1004.3273 (2010)
2000 – 2009
- 2009
- [j55]Wei Dai, Mona A. Sheikh, Olgica Milenkovic, Richard G. Baraniuk:
Compressive Sensing DNA Microarrays. EURASIP J. Bioinform. Syst. Biol. 2009 (2009) - [j54]Richard G. Baraniuk, Michael B. Wakin:
Random Projections of Smooth Manifolds. Found. Comput. Math. 9(1): 51-77 (2009) - [j53]Venkat Chandrasekaran, Michael B. Wakin, Dror Baron, Richard G. Baraniuk:
Representation and Compression of Multidimensional Piecewise Functions Using Surflets. IEEE Trans. Inf. Theory 55(1): 374-400 (2009) - [c101]Mark A. Davenport, Richard G. Baraniuk:
Sparse Geodesic Paths. AAAI Fall Symposium: Manifold Learning and Its Applications 2009 - [c100]Chinmay Hegde, Richard G. Baraniuk:
Compressive sensing of streams of pulses. Allerton 2009: 44-51 - [c99]Marco F. Duarte, Volkan Cevher, Richard G. Baraniuk:
Model-based compressive sensing for signal ensembles. Allerton 2009: 244-250 - [c98]Marco F. Duarte, Chinmay Hegde, Volkan Cevher, Richard G. Baraniuk:
Recovery of compressible signals in unions of subspaces. CISS 2009: 175-180 - [c97]Volkan Cevher, Petros Boufounos, Richard G. Baraniuk, Anna C. Gilbert, Martin J. Strauss:
Near-optimal Bayesian localization via incoherence and sparsity. IPSN 2009: 205-216 - [i6]Mark A. Davenport, Chinmay Hegde, Marco F. Duarte, Richard G. Baraniuk:
A Theoretical Analysis of Joint Manifolds. CoRR abs/0901.0760 (2009) - [i5]Dror Baron, Marco F. Duarte, Michael B. Wakin, Shriram Sarvotham, Richard G. Baraniuk:
Distributed Compressive Sensing. CoRR abs/0901.3403 (2009) - [i4]Joel A. Tropp, Jason N. Laska, Marco F. Duarte, Justin K. Romberg, Richard G. Baraniuk:
Beyond Nyquist: Efficient Sampling of Sparse Bandlimited Signals. CoRR abs/0902.0026 (2009) - [i3]Mark A. Davenport, Jason N. Laska, Petros Boufounos, Richard G. Baraniuk:
A simple proof that random matrices are democratic. CoRR abs/0911.0736 (2009) - 2008
- [j52]Richard G. Baraniuk, C. Sidney Burrus:
Viewpoint: Global warming toward open educational resources. Commun. ACM 51(9): 30-32 (2008) - [j51]Christopher J. Rozell, Don H. Johnson, Richard G. Baraniuk, Bruno A. Olshausen:
Sparse Coding via Thresholding and Local Competition in Neural Circuits. Neural Comput. 20(10): 2526-2563 (2008) - [j50]Christopher M. Kelty, C. Sidney Burrus, Richard G. Baraniuk:
Peer Review Anew: Three Principles and a Case Study in Postpublication Quality Assurance. Proc. IEEE 96(6): 1000-1011 (2008) - [j49]Richard G. Baraniuk, Emmanuel J. Candès, Robert D. Nowak, Martin Vetterli:
Compressive Sampling [From the Guest Editors]. IEEE Signal Process. Mag. 25(2): 12-13 (2008) - [j48]Marco F. Duarte, Mark A. Davenport, Dharmpal Takhar, Jason N. Laska, Ting Sun, Kevin F. Kelly, Richard G. Baraniuk:
Single-pixel imaging via compressive sampling. IEEE Signal Process. Mag. 25(2): 83-91 (2008) - [j47]Wai Lam Chan, Hyeokho Choi, Richard G. Baraniuk:
Coherent Multiscale Image Processing Using Dual-Tree Quaternion Wavelets. IEEE Trans. Image Process. 17(7): 1069-1082 (2008) - [c96]Wei Dai, Olgica Milenkovic, Mona A. Sheikh, Richard G. Baraniuk:
Probe Design for Compressive Sensing DNA Microarrays. BIBM 2008: 163-169 - [c95]Richard G. Baraniuk:
Compressive sensing. CISS 2008 - [c94]Petros Boufounos, Richard G. Baraniuk:
1-Bit compressive sensing. CISS 2008: 16-21 - [c93]Volkan Cevher, Aswin C. Sankaranarayanan, Marco F. Duarte, Dikpal Reddy, Richard G. Baraniuk, Rama Chellappa:
Compressive Sensing for Background Subtraction. ECCV (2) 2008: 155-168 - [c92]Volkan Cevher, Marco F. Duarte, Richard G. Baraniuk:
Distributed target localization via spatial sparsity. EUSIPCO 2008: 1-5 - [c91]Petros Boufounos, Richard G. Baraniuk:
Reconstructing sparse signals from their zero crossings. ICASSP 2008: 3361-3364 - [c90]Marco F. Duarte, Michael B. Wakin, Richard G. Baraniuk:
Wavelet-domain compressive signal reconstruction using a Hidden Markov Tree model. ICASSP 2008: 5137-5140 - [c89]Stephen Pfetsch, Tamer Ragheb, Jason N. Laska, Hamid Nejati, Anna C. Gilbert, Martin Strauss, Richard G. Baraniuk, Yehia Massoud:
On the feasibility of hardware implementation of sub-Nyquist random-sampling based analog-to-information conversion. ISCAS 2008: 1480-1483 - [c88]Volkan Cevher, Marco F. Duarte, Chinmay Hegde, Richard G. Baraniuk:
Sparse Signal Recovery Using Markov Random Fields. NIPS 2008: 257-264 - [i2]Richard G. Baraniuk, Volkan Cevher, Marco F. Duarte, Chinmay Hegde:
Model-Based Compressive Sensing. CoRR abs/0808.3572 (2008) - [i1]Dror Baron, Shriram Sarvotham, Richard G. Baraniuk:
Bayesian Compressive Sensing via Belief Propagation. CoRR abs/0812.4627 (2008) - 2007
- [j46]Ramesh Neelamani, Sanjeeb Dash, Richard G. Baraniuk:
On Nearly Orthogonal Lattice Bases and Random Lattices. SIAM J. Discret. Math. 21(1): 199-219 (2007) - [j45]Richard G. Baraniuk:
Compressive Sensing [Lecture Notes]. IEEE Signal Process. Mag. 24(4): 118-121 (2007) - [j44]Richard G. Baraniuk, C. Sidney Burrus, E. Joel Thierstein:
IEEE-SPS and Connexions - An Open Access Education Collaboration [Society News]. IEEE Signal Process. Mag. 24(6): 6-8 (2007) - [j43]Ramesh Neelamani, Max Deffenbaugh, Richard G. Baraniuk:
Texas Two-Step: A Framework for Optimal Multi-Input Single-Output Deconvolution. IEEE Trans. Image Process. 16(11): 2752-2765 (2007) - [c87]Mark A. Davenport, Marco F. Duarte, Michael B. Wakin, Jason N. Laska, Dharmpal Takhar, Kevin F. Kelly, Richard G. Baraniuk:
The smashed filter for compressive classification and target recognition. Computational Imaging 2007: 64980H - [c86]Petros Boufounos, Richard G. Baraniuk:
Quantization of Sparse Representations. DCC 2007: 378 - [c85]Marco F. Duarte, Mark A. Davenport, Michael B. Wakin, Jason N. Laska, Dharmpal Takhar, Kevin F. Kelly, Richard G. Baraniuk:
Multiscale Random Projections for Compressive Classification. ICIP (6) 2007: 161-164 - [c84]Christopher J. Rozell, Don H. Johnson, Richard G. Baraniuk, Bruno A. Olshausen:
Locally Competitive Algorithms for Sparse Approximation. ICIP (4) 2007: 169-172 - [c83]Mona A. Sheikh, Richard G. Baraniuk:
Blind Error-Free Detection of Transform-Domainwatermarks. ICIP (5) 2007: 453-456 - [c82]Jason N. Laska, Sami Kirolos, Marco F. Duarte, Tamer Ragheb, Richard G. Baraniuk, Yehia Massoud:
Theory and Implementation of an Analog-to-Information Converter using Random Demodulation. ISCAS 2007: 1959-1962 - [c81]Chinmay Hegde, Michael B. Wakin, Richard G. Baraniuk:
Random Projections for Manifold Learning. NIPS 2007: 641-648 - 2006
- [j42]Michael B. Wakin, Justin K. Romberg, Hyeokho Choi, Richard G. Baraniuk:
Wavelet-domain approximation and compression of piecewise smooth images. IEEE Trans. Image Process. 15(5): 1071-1087 (2006) - [j41]Ramesh Neelamani, Ricardo L. de Queiroz, Zhigang Fan, Sanjeeb Dash, Richard G. Baraniuk:
JPEG compression history estimation for color images. IEEE Trans. Image Process. 15(6): 1365-1378 (2006) - [j40]Dror Baron, Richard G. Baraniuk:
Faster sequential universal coding via block partitioning. IEEE Trans. Inf. Theory 52(4): 1708-1710 (2006) - [j39]Vinay J. Ribeiro, Rudolf H. Riedi, Richard G. Baraniuk:
Multiscale queueing analysis. IEEE/ACM Trans. Netw. 14(5): 1005-1018 (2006) - [j38]Véronique Delouille, Ramesh Neelamani, Richard G. Baraniuk:
Robust Distributed Estimation Using the Embedded Subgraphs Algorithm. IEEE Trans. Signal Process. 54(8): 2998-3010 (2006) - [c80]Raymond S. Wagner, Véronique Delouille, Richard G. Baraniuk:
Distributed Wavelet De-Noising for Sensor Networks. CDC 2006: 373-379 - [c79]Dharmpal Takhar, Jason N. Laska, Michael B. Wakin, Marco F. Duarte, Dror Baron, Shriram Sarvotham, Kevin F. Kelly, Richard G. Baraniuk:
A new compressive imaging camera architecture using optical-domain compression. Computational Imaging 2006: 606509 - [c78]Dror Baron, Shriram Sarvotham, Richard G. Baraniuk:
Coding vs. Packet Retransmission over Noisy Channels. CISS 2006: 537-541 - [c77]Marco F. Duarte, Mark A. Davenport, Michael B. Wakin, Richard G. Baraniuk:
Sparse Signal Detection from Incoherent Projections. ICASSP (3) 2006: 305-308 - [c76]Mark A. Davenport, Richard G. Baraniuk, Clayton D. Scott:
Controlling False Alarms With Support Vector Machines. ICASSP (5) 2006: 589-592 - [c75]Joel A. Tropp, Michael B. Wakin, Marco F. Duarte, Dror Baron, Richard G. Baraniuk:
Random Filters for Compressive Sampling and Reconstruction. ICASSP (3) 2006: 872-875 - [c74]Michael B. Wakin, Richard G. Baraniuk:
Random Projections of Signal Manifolds. ICASSP (5) 2006: 941-944 - [c73]Wai Lam Chan, Hyeokho Choi, Richard G. Baraniuk:
Multiscale Image Disparity Estimation using the Quaternion Wavelet Transform. ICIP 2006: 1229-1232 - [c72]Michael B. Wakin, Jason N. Laska, Marco F. Duarte, Dror Baron, Shriram Sarvotham, Dharmpal Takhar, Kevin F. Kelly, Richard G. Baraniuk:
An Architecture for Compressive Imaging. ICIP 2006: 1273-1276 - [c71]Marco F. Duarte, Michael B. Wakin, Dror Baron, Richard G. Baraniuk:
Universal distributed sensing via random projections. IPSN 2006: 177-185 - [c70]Raymond S. Wagner, Richard G. Baraniuk, Shu Du, David B. Johnson, Albert Cohen:
An architecture for distributed wavelet analysis and processing in sensor networks. IPSN 2006: 243-250 - [c69]Shriram Sarvotham, Dror Baron, Richard G. Baraniuk:
Sudocodes ߝ Fast Measurement and Reconstruction of Sparse Signals. ISIT 2006: 2804-2808 - 2005
- [j37]Shriram Sarvotham, Rudolf H. Riedi, Richard G. Baraniuk:
Network and user driven alpha-beta on-off source model for network traffic. Comput. Networks 48(3): 335-350 (2005) - [j36]Ivan W. Selesnick, Richard G. Baraniuk, Nick G. Kingsbury:
The dual-tree complex wavelet transform. IEEE Signal Process. Mag. 22(6): 123-151 (2005) - [c68]Santashil PalChaudhuri, Rajnish Kumar, Richard G. Baraniuk, David B. Johnson:
Design of Adaptive Overlays for Multi-scale Communication in Sensor Networks. DCOSS 2005: 173-190 - [c67]Raymond S. Wagner, Shriram Sarvotham, Richard G. Baraniuk:
A multiscale data representation for distributed sensor networks. ICASSP (4) 2005: 549-552 - [c66]Hyeokho Choi, Richard G. Baraniuk:
Multiscale manifold representation and modeling. ICASSP (4) 2005: 569-572 - [c65]Michael B. Wakin, David L. Donoho, Hyeokho Choi, Richard G. Baraniuk:
High-resolution navigation on non-differentiable image manifolds. ICASSP (5) 2005: 1073-1076 - [c64]R. King, Richard G. Baraniuk, Rudolf H. Riedi:
TCP-Africa: an adaptive and fair rapid increase rule for scalable TCP. INFOCOM 2005: 1838-1848 - [c63]Michael B. Wakin, Marco F. Duarte, Shriram Sarvotham, Dror Baron, Richard G. Baraniuk:
Recovery of Jointly Sparse Signals from Few Random Projections. NIPS 2005: 1433-1440 - 2004
- [j35]Vinay J. Ribeiro, Rudolf H. Riedi, Richard G. Baraniuk:
Locating Available Bandwidth Bottlenecks. IEEE Internet Comput. 8(5): 34-41 (2004) - [j34]Hyeokho Choi, Richard G. Baraniuk:
Multiple wavelet basis image denoising using Besov ball projections. IEEE Signal Process. Lett. 11(9): 717-720 (2004) - [j33]Richard G. Baraniuk, C. Sidney Burrus, Don H. Johnson, Douglas L. Jones:
Sharing knowledge and building communities in signal processing. IEEE Signal Process. Mag. 21(5): 10-16 (2004) - [j32]Rohit V. Gaikwad, Richard G. Baraniuk:
Joint signaling techniques and spectral optimization for symmetric bit-rate communication over self-NEXT-dominated channels. IEEE Trans. Commun. 52(7): 1080-1083 (2004) - [j31]Ramesh Neelamani, Hyeokho Choi, Richard G. Baraniuk:
ForWaRD: Fourier-wavelet regularized deconvolution for ill-conditioned systems. IEEE Trans. Signal Process. 52(2): 418-433 (2004) - [c62]Nadeem Ahmed, Mohammad Ali Khojestapour, Richard G. Baraniuk:
Delay-limited throughput maximization for fading channels using rate and power control. GLOBECOM 2004: 3459-3463 - [c61]Mohammad Ali Khojastepour, Behnaam Aazhang, Richard G. Baraniuk:
Contraction, smoothness, and low-pass filtering. ICASSP (2) 2004: 897-900 - [c60]Felix C. A. Fernandes, Michael B. Wakin, Richard G. Baraniuk:
Non-redundant, linear-phase, semi-orthogonal, directional complex wavelets [image/video processing applications]. ICASSP (2) 2004: 953-956 - [c59]Wai Lam Chan, Hyeokho Choi, Richard G. Baraniuk:
Directional hypercomplex wavelets for multidimensional signal analysis and processing. ICASSP (3) 2004: 996-999 - [c58]Wai Lam Chan, Hyeokho Choi, Richard G. Baraniuk:
Quaternion wavelets for image analysis and processing. ICIP 2004: 3057-3060 - [c57]Véronique Delouille, Ramesh Neelamani, Richard G. Baraniuk:
Robust distributed estimation in sensor networks using the embedded polygons algorithm. IPSN 2004: 405-413 - [c56]Venkat Chandrasekaran, Michael B. Wakin, Dror Baron, Richard G. Baraniuk:
Surflets: a sparse representation for multidimensional functions containing smooth discontinuities. ISIT 2004: 563 - [c55]Vinay J. Ribeiro, Rudolf H. Riedi, Richard G. Baraniuk:
Spatio-temporal available bandwidth estimation with STAB. SIGMETRICS 2004: 394-395 - 2003
- [j30]Roger L. Claypoole Jr., Geoffrey M. Davis, Wim Sweldens, Richard G. Baraniuk:
Nonlinear wavelet transforms for image coding via lifting. IEEE Trans. Image Process. 12(12): 1449-1459 (2003) - [c54]Sridhar Lavu, Hyeokho Choi, Richard G. Baraniuk:
Estimation-Quantization Geometry Coding Using Normal Meshes. DCC 2003: 362-371 - [c53]Rutger L. van Spaendonck, Thierry Blu, Richard G. Baraniuk, Martin Vetterli:
Orthogonal Hilbert transform filter banks and wavelets. ICASSP (6) 2003: 505-508 - [c52]Swaroop Appadwedula, Richard G. Baraniuk, Matthew Berry, Mark D. Butala, Hyeokho Choi, Mark A. Haun, Douglas L. Jones, Michael L. Kramer, Dima Moussa, Lee C. Potter, Daniel Grobe Sachs, Brian Wade, Raymond S. Wagner:
Open-content signal processing laboratories in connexions. ICASSP (3) 2003: 777-780 - [c51]Justin K. Romberg, Michael B. Wakin, Richard G. Baraniuk:
Approximation and compression of piecewise smooth images using a wavelet/wedgelet geometric model. ICIP (1) 2003: 49-52 - [c50]Ramesh Neelamani, Ricardo L. de Queiroz, Zhigang Fan, Richard G. Baraniuk:
JPEG compression history estimation for color images. ICIP (3) 2003: 245-248 - [c49]Raymond S. Wagner, Robert D. Nowak, Richard G. Baraniuk:
Distributed image compression for sensor networks using correspondence analysis and super-resolution. ICIP (1) 2003: 597-600 - [c48]Sridhar Lavu, Hyeokho Choi, Richard G. Baraniuk:
Geometry Compression of Normal Meshes Using Rate-Distortion Algorithms. Symposium on Geometry Processing 2003: 52-61 - [c47]Justin K. Romberg, Michael B. Wakin, Richard G. Baraniuk:
Multiscale geometric image processing. VCIP 2003: 1265-1272 - 2002
- [j29]Richard G. Baraniuk, Ronald A. DeVore, George Kyriazis, X. M. Yu:
Near Best Tree Approximation. Adv. Comput. Math. 16(4): 357-373 (2002) - [j28]Patrice Abry, Richard G. Baraniuk, Patrick Flandrin, Rudolf H. Riedi, Darryl Veitch:
Multiscale nature of network traffic. IEEE Signal Process. Mag. 19(3): 28-46 (2002) - [c46]Michael B. Wakin, Justin K. Romberg, Hyeokho Choi, Richard G. Baraniuk:
Image Compression using an Efficient Edge Cartoon + Texture Model. DCC 2002: 43- - [c45]Nadeem Ahmed, Richard G. Baraniuk:
Asymptotic performance of transmit diversity via OFDM for multipath channels. GLOBECOM 2002: 691-695 - [c44]Shriram Sarvotham, Xin Wang, Rudolf H. Riedi, Richard G. Baraniuk:
Additive and multiplicative mixture trees for network traffic modeling. ICASSP 2002: 4040-4043 - [c43]Richard G. Baraniuk, C. Sidney Burrus, B. M. Hendricks, G. L. Henry, Alfred O. Hero III, Don H. Johnson, Douglas L. Jones, Julius Kusuma, Robert D. Nowak, J. E. Odegard, Lee C. Potter, Kannan Ramchandran, R. J. Reedstrom, Philip Schniter, Ivan W. Selesnick, Douglas B. Williams, W. L. Wilson:
Connexions: DSP education for a networked world. ICASSP 2002: 4144-4147 - [c42]Justin K. Romberg, Michael B. Wakin, Hyeokho Choi, Richard G. Baraniuk:
Rate-distortion optimized image compression using wedgelets. ICIP (3) 2002: 237-240 - [c41]Justin K. Romberg, Michael B. Wakin, Richard G. Baraniuk:
Multiscale wedgelet image analysis: fast decompositions and modeling. ICIP (3) 2002: 585-588 - 2001
- [j27]Justin K. Romberg, Hyeokho Choi, Richard G. Baraniuk:
Bayesian tree-structured image modeling using wavelet-domain hidden Markov models. IEEE Trans. Image Process. 10(7): 1056-1068 (2001) - [j26]Hyeokho Choi, Richard G. Baraniuk:
Multiscale image segmentation using wavelet-domain hidden Markov models. IEEE Trans. Image Process. 10(9): 1309-1321 (2001) - [j25]Richard G. Baraniuk, Patrick Flandrin, Augustus J. E. M. Janssen, Olivier J. J. Michel:
Measuring time-Frequency information content using the Rényi entropies. IEEE Trans. Inf. Theory 47(4): 1391-1409 (2001) - [j24]Richard G. Baraniuk, Mark Coates, Philippe Steeghs:
Hybrid linear/quadratic time-frequency attributes. IEEE Trans. Signal Process. 49(4): 760-766 (2001) - [c40]Nadeem Ahmed, Richard G. Baraniuk, Donald P. Shaver:
Optimal transmit spectra for communication in the presence of crosstalk and imperfect echo cancellation. GLOBECOM 2001: 364-368 - [c39]Vinay J. Ribeiro, Rudolf H. Riedi, Richard G. Baraniuk:
Wavelets and multifractals for network traffic modeling and inference. ICASSP 2001: 3429-3432 - [c38]M. Jansen, Hyeokho Choi, Sridhar Lavu, Richard G. Baraniuk:
Multiscale image processing using normal triangulated meshes. ICIP (2) 2001: 229-232 - [c37]Justin K. Romberg, Hyeokho Choi, Richard G. Baraniuk:
Multiscale edge grammars for complex wavelet transforms. ICIP (1) 2001: 614-617 - [c36]Ramesh Neelamani, Ricardo L. de Queiroz, Richard G. Baraniuk:
Compression color space estimation of JPEG images using lattice basis reduction. ICIP (1) 2001: 890-893 - [c35]Shriram Sarvotham, Rudolf H. Riedi, Richard G. Baraniuk:
Connection-level analysis and modeling of network traffic. Internet Measurement Workshop 2001: 99-103 - [c34]Ramesh Neelamani, Ricardo L. de Queiroz, Richard G. Baraniuk:
Lattice algorithms for compression color space estimation in JPEG images. IWCIA 2001: 245-254 - 2000
- [c33]Hyeokho Choi, Richard G. Baraniuk:
Multiscale document segmentation using wavelet-domain hidden Markov models. Document Recognition and Retrieval 2000: 234-247 - [c32]Hyeokho Choi, Justin K. Romberg, Richard G. Baraniuk, Nick G. Kingsbury:
Hidden Markov tree modeling of complex wavelet transforms. ICASSP 2000: 133-136 - [c31]Jun Feng Tian, Richard G. Baraniuk, Raymond O. Wells Jr., Damian M. Tan, Hong Ren Wu:
Wavelet folding and decorrelation across the scale. ICASSP 2000: 544-547 - [c30]Richard G. Baraniuk, Mark Coates, Philippe Steeghs:
Hybrid linear/quadratic time-frequency attributes. ICASSP 2000: 681-684 - [c29]Justin K. Romberg, Hyeokho Choi, Richard G. Baraniuk, Nick G. Kingsbury:
Multiscale Classification Using Complex Wavelets and Hidden Markov Tree Models. ICIP 2000: 371-374 - [c28]Timothy Dorney, Jon Johnson, Daniel M. Mittleman, Richard G. Baraniuk:
Imaging with THZ Pulses. ICIP 2000: 764-767 - [c27]Ramesh Neelamani, Robert D. Nowak, Richard G. Baraniuk:
Model-Based Inverse Halftoning with Wavelet-Vaguelette Deconvolution. ICIP 2000: 973-976 - [c26]Vinay J. Ribeiro, Rudolf H. Riedi, Matthew S. Crouse, Richard G. Baraniuk:
Multiscale Queuing Analysis of Long-Range-Dependent Network Traffic. INFOCOM 2000: 1026-1035 - [c25]Timothy Dorney, Richard G. Baraniuk, Daniel M. Mittleman, Robert D. Nowak:
Spectroscopic Imaging Using Terahertz Time-Domain Signals. SSIAI 2000: 151-155 - [c24]Justin K. Romberg, Hyeokho Choi, Richard G. Baraniuk:
Bayesian Tree-Structured Image Modeling. SSIAI 2000: 232-236
1990 – 1999
- 1999
- [j23]Robert D. Nowak, Richard G. Baraniuk:
Wavelet-domain filtering for photon imaging systems. IEEE Trans. Image Process. 8(5): 666-678 (1999) - [j22]Rudolf H. Riedi, Matthew S. Crouse, Vinay J. Ribeiro, Richard G. Baraniuk:
A Multifractal Wavelet Model with Application to Network Traffic. IEEE Trans. Inf. Theory 45(3): 992-1018 (1999) - [j21]Martin Pasquier, Paulo Gonçalves, Richard G. Baraniuk:
Hybrid linear/bilinear time-scale analysis. IEEE Trans. Signal Process. 47(1): 254-259 (1999) - [j20]Robert D. Nowak, Richard G. Baraniuk:
Wavelet-based transformations for nonlinear signal processing. IEEE Trans. Signal Process. 47(7): 1852-1865 (1999) - [c23]Hyeokho Choi, Richard G. Baraniuk:
Interpolation and denoising of nonuniformly sampled data using wavelet-domain processing. ICASSP 1999: 1645-1648 - [c22]Ramesh Neelamani, Hyeokho Choi, Richard G. Baraniuk:
Wavelet-based deconvolution for ill-conditioned systems. ICASSP 1999: 3241-3244 - [c21]Justin K. Romberg, Hyeokho Choi, Richard G. Baraniuk:
Bayesian Wavelet-Domain Image Modeling Using Hidden Markov Trees. ICIP (1) 1999: 158-162 - [c20]Ramesh Neelamani, Hyeokho Choi, Richard G. Baraniuk:
Wavelet-Domain Regularized Deconvolution for ILL-Conditioned Systems. ICIP (1) 1999: 204-208 - [c19]Hyeokho Choi, Richard G. Baraniuk:
Multiple Basis Wavelet Denoising Using BESOV Projections. ICIP (1) 1999: 595-599 - [c18]Vinay J. Ribeiro, Rudolf H. Riedi, Matthew S. Crouse, Richard G. Baraniuk:
Simulation of nonGaussian Long-Range-Dependent Traffic Using Wavelets. SIGMETRICS 1999: 1-12 - 1998
- [j19]Richard G. Baraniuk:
Joint Distributions of Arbitrary Variables Made Easy. Multidimens. Syst. Signal Process. 9(4): 341-348 (1998) - [j18]Robert D. Nowak, Richard G. Baraniuk:
Adaptive weighted highpass filters using multiscale analysis. IEEE Trans. Image Process. 7(7): 1068-1074 (1998) - [j17]Matthew S. Crouse, Robert D. Nowak, Richard G. Baraniuk:
Wavelet-based statistical signal processing using hidden Markov models. IEEE Trans. Signal Process. 46(4): 886-902 (1998) - [j16]Paulo Gonçalves, Richard G. Baraniuk:
Pseudo affine Wigner distributions: definition and kernel formulation. IEEE Trans. Signal Process. 46(6): 1505-1516 (1998) - [j15]Richard G. Baraniuk:
Beyond time-frequency analysis: energy densities in one and many dimensions. IEEE Trans. Signal Process. 46(9): 2305-2314 (1998) - [c17]Roger Claypool, Geoffrey M. Davis, Wim Sweldens, Richard G. Baraniuk:
Adaptive Wavelet Transforms for Image Coding Using Lifting. Data Compression Conference 1998: 537 - [c16]Roger L. Claypoole Jr., Richard G. Baraniuk, Robert D. Nowak:
Adaptive wavelet transforms via lifting. ICASSP 1998: 1513-1516 - [c15]Matthew S. Crouse, Richard G. Baraniuk:
Simplified wavelet-domain hidden Markov models using contexts. ICASSP 1998: 2277-2280 - 1997
- [c14]Robert D. Nowak, Richard G. Baraniuk:
Wavelet-based transformations for nonlinear signal processing. ICASSP 1997: 2385-2388 - [c13]Matthew S. Crouse, Richard G. Baraniuk, Robert D. Nowak:
Signal estimation using wavelet-Markov models. ICASSP 1997: 3429-3432 - [c12]Don H. Johnson, Paulo Gonçalves, Richard G. Baraniuk:
Improved type-based detection of analog signals. ICASSP 1997: 3717-3720 - 1996
- [j14]Richard G. Baraniuk:
A limitation of the kernel method for joint distributions of arbitrary variables. IEEE Signal Process. Lett. 3(2): 51-53 (1996) - [j13]Richard G. Baraniuk:
Covariant time-frequency representations through unitary equivalence. IEEE Signal Process. Lett. 3(3): 79-81 (1996) - [j12]Paulo Gonçalves, Richard G. Baraniuk:
A pseudo-Bertrand distribution for time-scale analysis. IEEE Signal Process. Lett. 3(3): 82-84 (1996) - [j11]Kristin A. Farry, Ian D. Walker, Richard G. Baraniuk:
Myoelectric teleoperation of a complex robotic hand. IEEE Trans. Robotics Autom. 12(5): 775-788 (1996) - [j10]Richard G. Baraniuk, Douglas L. Jones:
Wigner-based formulation of the chirplet transform. IEEE Trans. Signal Process. 44(12): 3129-3135 (1996) - [c11]L. Fridtjof Wisur-Olsen, Richard G. Baraniuk:
Optimal phase kernels for time-frequency analysis. ICASSP 1996: 1419-1422 - [c10]Paulo Gonçalves, Richard G. Baraniuk:
Pseudo affine Wigner distributions. ICASSP 1996: 1423-1426 - 1995
- [j9]Richard G. Baraniuk, Leon Cohen:
On joint distributions for arbitrary variables. IEEE Signal Process. Lett. 2(1): 10-12 (1995) - [j8]Richard G. Baraniuk, Douglas L. Jones:
Unitary equivalence: a new twist on signal processing. IEEE Trans. Signal Process. 43(10): 2269-2282 (1995) - [j7]Douglas L. Jones, Richard G. Baraniuk:
An adaptive optimal-kernel time-frequency representation. IEEE Trans. Signal Process. 43(10): 2361-2371 (1995) - [c9]Richard G. Baraniuk:
Marginals vs. covariance in joint distribution theory. ICASSP 1995: 1021-1024 - [c8]Richard G. Baraniuk:
Warping time-frequency and time-scale representations to match signals. Visual Information Processing 1995: 34-45 - 1994
- [j6]Richard G. Baraniuk, Douglas L. Jones:
A signal-dependent time-frequency representation: fast algorithm for optimal kernel design. IEEE Trans. Signal Process. 42(1): 134-146 (1994) - [j5]Douglas L. Jones, Richard G. Baraniuk:
A simple scheme for adapting time-frequency representations. IEEE Trans. Signal Process. 42(12): 3530-3535 (1994) - [c7]Patrick Flandrin, Richard G. Baraniuk, Olivier J. J. Michel:
Time-frequency complexity and information. ICASSP (3) 1994: 329-332 - [c6]Richard G. Baraniuk:
Beyond time-frequency analysis: energy densities in one and many dimensions. ICASSP (3) 1994: 357-360 - [c5]Richard G. Baraniuk:
Wavelet Soft-Thresholding of Time-Frequency Representations. ICIP (1) 1994: 71-74 - 1993
- [j4]Richard G. Baraniuk, Douglas L. Jones:
Signal-dependent time-frequency analysis using a radially Gaussian kernel. Signal Process. 32(3): 263-284 (1993) - [j3]Richard G. Baraniuk, Douglas L. Jones:
A signal-dependent time-frequency representation: optimal kernel design. IEEE Trans. Signal Process. 41(4): 1589-1602 (1993) - [j2]Richard G. Baraniuk, Douglas L. Jones:
Shear madness: new orthonormal bases and frames using chirp functions. IEEE Trans. Signal Process. 41(12): 3543-3549 (1993) - [c4]Douglas L. Jones, Richard G. Baraniuk:
An adaptive optimal-kernel time-frequency representation. ICASSP (4) 1993: 109-112 - [c3]Richard G. Baraniuk, Douglas L. Jones:
Warped wavelet bases: unitary equivalence and signal processing. ICASSP (3) 1993: 320-323 - 1992
- [b1]Richard G. Baraniuk:
Shear Madness: Signal-Dependent and Metaplectic Time-Frequency Representations. University of Illinois Urbana-Champaign, USA, 1992 - [c2]Richard G. Baraniuk, Douglas L. Jones:
New dimensions in wavelet analysis. ICASSP 1992: 137-140 - 1991
- [c1]Richard G. Baraniuk, Douglas L. Jones:
A radially-Gaussian, signal-dependent time-frequency representation. ICASSP 1991: 3181-3184
1980 – 1989
- 1989
- [j1]Barry D. Van Veen, Richard G. Baraniuk:
Matrix based computation of floating-point roundoff noise. IEEE Trans. Acoust. Speech Signal Process. 37(12): 1995-1998 (1989)
Coauthor Index
[j123] [c253] [i173] [i166] [i162] [c245] [i156] [i147] [j113] [j112] [c233] [c230] [c226] [c224] [c223] [c221] [i142] [i140] [i139] [i138] [i137] [i134] [i129] [j108] [c207] [c205] [c203] [c202] [i122] [i120] [i108] [i107] [j102] [c189] [i103] [i95] [i94] [i93] [i92] [i89] [i88] [i87] [i86] [c184] [c181] [c180] [i81] [i78] [c175] [c174] [i72] [i70] [i66] [i59] [i58] [i57]
Tom Goldstein
aka: Thomas A. Goldstein
aka: Thomas A. Goldstein
[c231] [c227] [i136] [i133] [c214] [c210] [c209] [c208] [e3] [i117] [i112] [c196] [c195] [e2] [i101] [i100] [c186] [c185] [e1] [i80] [j99] [c177] [c172] [j96] [c169] [c168] [c167] [c166] [c164] [c161] [c159] [i63] [i62] [c157] [c156] [c153] [i56] [c144] [i52] [j84] [c140] [c138] [c137] [i32] [i31] [c136] [c135] [c134] [i28] [i27] [i22]
Tan M. Nguyen
aka: Tan Minh Nguyen
aka: Tan Minh Nguyen
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