default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDAarti Singh
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2025
[i84]Nuoya Xiong, Aarti Singh:
Projection Optimization: A General Framework for Multi-Objective and Multi-Group RLHF. CoRR abs/2502.15145 (2025)- 2024
- [j28]Eric Luxenberg
, Dhruv Malik, Yuanzhi Li, Aarti Singh, Stephen P. Boyd:
Specifying and Solving Robust Empirical Risk Minimization Problems Using CVXPY. J. Optim. Theory Appl. 202(3): 1158-1168 (2024) - [j27]Aarti Singh, Neal Patwari:
Online Learning for Dynamic Impending Collision Prediction using FMCW Radar. ACM Trans. Internet Things 5(1): 2:1-2:26 (2024) - [c89]Kanad Pardeshi, Itai Shapira, Ariel D. Procaccia, Aarti Singh:
Learning Decision-Making Functions Given Cardinal and Ordinal Consensus Data. AAAI Spring Symposia 2024: 572 - [c88]Jennifer Hsia, Danish Pruthi, Aarti Singh, Zachary C. Lipton:
Goodhart's Law Applies to NLP's Explanation Benchmarks. EACL (Findings) 2024: 1322-1335 - [c87]Aakash Lahoti, Stefani Karp, Ezra Winston, Aarti Singh, Yuanzhi Li:
Role of Locality and Weight Sharing in Image-Based Tasks: A Sample Complexity Separation between CNNs, LCNs, and FCNs. ICLR 2024 - [c86]Yuda Song, Drew Bagnell, Aarti Singh:
Hybrid Reinforcement Learning from Offline Observation Alone. ICML 2024 - [c85]Yuda Song, Gokul Swamy, Aarti Singh, J. Andrew Bagnell, Wen Sun:
The Importance of Online Data: Understanding Preference Fine-tuning via Coverage. NeurIPS 2024 - [c84]Kanad Pardeshi, Itai Shapira, Ariel D. Procaccia, Aarti Singh:
Learning Social Welfare Functions. NeurIPS 2024 - [i83]Aakash Lahoti, Stefani Karp, Ezra Winston, Aarti Singh, Yuanzhi Li:
Role of Locality and Weight Sharing in Image-Based Tasks: A Sample Complexity Separation between CNNs, LCNs, and FCNs. CoRR abs/2403.15707 (2024) - [i82]Kanad Shrikar Pardeshi, Itai Shapira, Ariel D. Procaccia, Aarti Singh:
Learning Social Welfare Functions. CoRR abs/2405.17700 (2024) - [i81]Yuda Song, Gokul Swamy, Aarti Singh, J. Andrew Bagnell, Wen Sun:
Understanding Preference Fine-Tuning Through the Lens of Coverage. CoRR abs/2406.01462 (2024) - [i80]Yuda Song, J. Andrew Bagnell, Aarti Singh:
Hybrid Reinforcement Learning from Offline Observation Alone. CoRR abs/2406.07253 (2024) - [i79]Youngseog Chung, Dhruv Malik, Jeff G. Schneider, Yuanzhi Li, Aarti Singh:
Beyond Parameter Count: Implicit Bias in Soft Mixture of Experts. CoRR abs/2409.00879 (2024) - [i78]Santiago Cortes-Gomez, Naveen Raman, Aarti Singh, Bryan Wilder:
Data-driven Design of Randomized Control Trials with Guaranteed Treatment Effects. CoRR abs/2410.11212 (2024) - [i77]Ojash Neopane, Aaditya Ramdas, Aarti Singh:
Logarithmic Neyman Regret for Adaptive Estimation of the Average Treatment Effect. CoRR abs/2411.14341 (2024) - 2023
- [j26]Phillip Smith, Anh Luong, Shamik Sarkar, Harsimran Singh, Aarti Singh, Neal Patwari, Sneha Kumar Kasera, Kurt Derr:
A Novel Software Defined Radio for Practical, Mobile Crowdsourced Spectrum Sensing. IEEE Trans. Mob. Comput. 22(3): 1289-1300 (2023) - [c83]Yusha Liu, Aarti Singh:
Adaptation to Misspecified Kernel Regularity in Kernelised Bandits. AISTATS 2023: 4963-4985 - [c82]Dhruv Malik, Conor Igoe, Yuanzhi Li, Aarti Singh:
Weighted Tallying Bandits: Overcoming Intractability via Repeated Exposure Optimality. ICML 2023: 23590-23609 - [c81]Anirudh Vemula, Yuda Song, Aarti Singh, Drew Bagnell, Sanjiban Choudhury:
The Virtues of Laziness in Model-based RL: A Unified Objective and Algorithms. ICML 2023: 34978-35005 - [i76]Anirudh Vemula, Yuda Song, Aarti Singh, J. Andrew Bagnell, Sanjiban Choudhury:
The Virtues of Laziness in Model-based RL: A Unified Objective and Algorithms. CoRR abs/2303.00694 (2023) - [i75]Vaibhav Jindal, Drew Jamieson, Albert Liang, Aarti Singh, Shirley Ho:
Predicting the Initial Conditions of the Universe using Deep Learning. CoRR abs/2303.13056 (2023) - [i74]Yusha Liu, Aarti Singh:
Adaptation to Misspecified Kernel Regularity in Kernelised Bandits. CoRR abs/2304.13830 (2023) - [i73]Dhruv Malik, Conor Igoe, Yuanzhi Li, Aarti Singh:
Weighted Tallying Bandits: Overcoming Intractability via Repeated Exposure Optimality. CoRR abs/2305.02955 (2023) - [i72]Shivani Chiranjeevi, Mojdeh Saadati, Zi K. Deng, Jayanth Koushik, Talukder Z. Jubery, Daren Mueller, Matthew E. O. Neal, Nirav C. Merchant, Aarti Singh, Asheesh K. Singh, Soumik Sarkar, Arti Singh, Baskar Ganapathysubramanian:
Deep learning powered real-time identification of insects using citizen science data. CoRR abs/2306.02507 (2023) - [i71]Eric Luxenberg, Dhruv Malik, Yuanzhi Li, Aarti Singh, Stephen P. Boyd:
Specifying and Solving Robust Empirical Risk Minimization Problems Using CVXPY. CoRR abs/2306.05649 (2023) - [i70]Jennifer Hsia, Danish Pruthi, Aarti Singh, Zachary C. Lipton:
Goodhart's Law Applies to NLP's Explanation Benchmarks. CoRR abs/2308.14272 (2023) - 2022
- [j25]Charvi Rastogi, Sivaraman Balakrishnan, Nihar B. Shah, Aarti Singh:
Two-Sample Testing on Ranked Preference Data and the Role of Modeling Assumptions. J. Mach. Learn. Res. 23: 225:1-225:48 (2022) - [j24]Yusha Liu, Yichong Xu, Nihar B. Shah, Aarti Singh:
Integrating Rankings into Quantized Scores in Peer Review. Trans. Mach. Learn. Res. 2022 (2022) - [c80]Dhruv Malik, Yuanzhi Li, Aarti Singh:
Complete Policy Regret Bounds for Tallying Bandits. COLT 2022: 5146-5174 - [i69]Yusha Liu, Yichong Xu, Nihar B. Shah, Aarti Singh:
Integrating Rankings into Quantized Scores in Peer Review. CoRR abs/2204.03505 (2022) - [i68]Dhruv Malik, Yuanzhi Li, Aarti Singh:
Complete Policy Regret Bounds for Tallying Bandits. CoRR abs/2204.11174 (2022) - 2021
- [j23]Ivan Stelmakh, Nihar B. Shah, Aarti Singh:
PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review. J. Mach. Learn. Res. 22: 163:1-163:66 (2021) - [j22]Zeyuan Allen-Zhu, Yuanzhi Li, Aarti Singh, Yining Wang:
Near-optimal discrete optimization for experimental design: a regret minimization approach. Math. Program. 186(1): 439-478 (2021) - [j21]Ivan Stelmakh, Nihar B. Shah, Aarti Singh, Hal Daumé III:
Prior and Prejudice: The Novice Reviewers' Bias against Resubmissions in Conference Peer Review. Proc. ACM Hum. Comput. Interact. 5(CSCW1): 75:1-75:17 (2021) - [c79]Ivan Stelmakh, Nihar B. Shah, Aarti Singh, Hal Daumé III:
A Novice-Reviewer Experiment to Address Scarcity of Qualified Reviewers in Large Conferences. AAAI 2021: 4785-4793 - [c78]Ivan Stelmakh, Nihar B. Shah, Aarti Singh:
Catch Me if I Can: Detecting Strategic Behaviour in Peer Assessment. AAAI 2021: 4794-4802 - [c77]Ojash Neopane, Aaditya Ramdas, Aarti Singh:
Best Arm Identification under Additive Transfer Bandits. ACSCC 2021: 464-470 - [c76]Yusha Liu, Yining Wang, Aarti Singh:
Smooth Bandit Optimization: Generalization to Holder Space. AISTATS 2021: 2206-2214 - [c75]Aarti Singh, Neal Patwari:
Range-based Collision Prediction for Dynamic Motion. CCNC 2021: 1-6 - [c74]Stefani Karp, Ezra Winston, Yuanzhi Li, Aarti Singh:
Local Signal Adaptivity: Provable Feature Learning in Neural Networks Beyond Kernels. NeurIPS 2021: 24883-24897 - [i67]Ojash Neopane, Aaditya Ramdas, Aarti Singh:
Best Arm Identification under Additive Transfer Bandits. CoRR abs/2112.04083 (2021) - 2020
- [j20]Yichong Xu, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski:
Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information. J. Mach. Learn. Res. 21: 162:1-162:54 (2020) - [c73]Yichong Xu, Xi Chen, Aarti Singh, Artur Dubrawski:
Thresholding Bandit Problem with Both Duels and Pulls. AISTATS 2020: 2591-2600 - [c72]Charvi Rastogi, Sivaraman Balakrishnan, Nihar B. Shah, Aarti Singh:
Two-Sample Testing on Pairwise Comparison Data and the Role of Modeling Assumptions. ISIT 2020: 1271-1276 - [c71]Yichong Xu, Ruosong Wang, Lin F. Yang, Aarti Singh, Artur Dubrawski:
Preference-based Reinforcement Learning with Finite-Time Guarantees. NeurIPS 2020 - [c70]Yichong Xu, Aparna Joshi, Aarti Singh, Artur Dubrawski:
Zeroth Order Non-convex optimization with Dueling-Choice Bandits. UAI 2020: 899-908 - [i66]Yichong Xu, Ruosong Wang, Lin F. Yang, Aarti Singh, Artur Dubrawski:
Preference-based Reinforcement Learning with Finite-Time Guarantees. CoRR abs/2006.08910 (2020) - [i65]Charvi Rastogi, Sivaraman Balakrishnan, Nihar B. Shah, Aarti Singh:
Two-Sample Testing on Ranked Preference Data and the Role of Modeling Assumptions. CoRR abs/2006.11909 (2020) - [i64]Ivan Stelmakh, Nihar B. Shah, Aarti Singh:
Catch Me if I Can: Detecting Strategic Behaviour in Peer Assessment. CoRR abs/2010.04041 (2020) - [i63]Ivan Stelmakh, Nihar B. Shah, Aarti Singh, Hal Daumé III:
Prior and Prejudice: The Novice Reviewers' Bias against Resubmissions in Conference Peer Review. CoRR abs/2011.14646 (2020) - [i62]Ivan Stelmakh, Nihar B. Shah, Aarti Singh, Hal Daumé III:
A Novice-Reviewer Experiment to Address Scarcity of Qualified Reviewers in Large Conferences. CoRR abs/2011.15050 (2020) - [i61]Ivan Stelmakh, Charvi Rastogi, Nihar B. Shah, Aarti Singh, Hal Daumé III:
A Large Scale Randomized Controlled Trial on Herding in Peer-Review Discussions. CoRR abs/2011.15083 (2020) - [i60]Yusha Liu, Yining Wang, Aarti Singh:
Smooth Bandit Optimization: Generalization to Hölder Space. CoRR abs/2012.06076 (2020)
2010 – 2019
- 2019
- [j19]Aarti Singh, Dimple Juneja, Rashmi Singh, Saurabh Mukherjee:
A clustered neighbourhood consensus algorithm for a generic agent interaction protocol. Int. J. Adv. Intell. Paradigms 12(3/4): 305-316 (2019) - [j18]Yining Wang, Jialei Wang, Sivaraman Balakrishnan, Aarti Singh:
Rate optimal estimation and confidence intervals for high-dimensional regression with missing covariates. J. Multivar. Anal. 174 (2019) - [j17]Yining Wang, Yu-Xiang Wang, Aarti Singh:
A Theoretical Analysis of Noisy Sparse Subspace Clustering on Dimensionality-Reduced Data. IEEE Trans. Inf. Theory 65(2): 685-706 (2019) - [j16]Yining Wang, Sivaraman Balakrishnan, Aarti Singh:
Optimization of Smooth Functions With Noisy Observations: Local Minimax Rates. IEEE Trans. Inf. Theory 65(11): 7350-7366 (2019) - [c69]Yifan Wu, Barnabás Póczos, Aarti Singh:
Towards Understanding the Generalization Bias of Two Layer Convolutional Linear Classifiers with Gradient Descent. AISTATS 2019: 1070-1078 - [c68]Ivan Stelmakh, Nihar B. Shah, Aarti Singh:
PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review. ALT 2019: 827-855 - [c67]Simon S. Du, Xiyu Zhai, Barnabás Póczos, Aarti Singh:
Gradient Descent Provably Optimizes Over-parameterized Neural Networks. ICLR (Poster) 2019 - [c66]Ivan Stelmakh, Nihar B. Shah, Aarti Singh:
On Testing for Biases in Peer Review. NeurIPS 2019: 5287-5297 - [i59]Yichong Xu, Xi Chen, Aarti Singh, Artur Dubrawski:
Thresholding Bandit Problem with Both Duels and Pulls. CoRR abs/1910.06368 (2019) - [i58]Yuexin Wu, Yichong Xu, Aarti Singh, Yiming Yang, Artur Dubrawski:
Active Learning for Graph Neural Networks via Node Feature Propagation. CoRR abs/1910.07567 (2019) - [i57]Yichong Xu, Aparna Joshi, Aarti Singh, Artur Dubrawski:
Zeroth Order Non-convex optimization with Dueling-Choice Bandits. CoRR abs/1911.00980 (2019) - 2018
- [j15]Aarti Singh, Anu Sharma:
A clustering-based recommendation engine for restaurants. Int. J. Adv. Intell. Paradigms 11(3/4): 272-283 (2018) - [j14]Martin Azizyan, Akshay Krishnamurthy, Aarti Singh:
Extreme Compressive Sampling for Covariance Estimation. IEEE Trans. Inf. Theory 64(12): 7613-7635 (2018) - [c65]Yichong Xu, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski:
Interactive Linear Regression with Pairwise Comparisons. ACSSC 2018: 636-640 - [c64]Yining Wang, Simon S. Du, Sivaraman Balakrishnan, Aarti Singh:
Stochastic Zeroth-order Optimization in High Dimensions. AISTATS 2018: 1356-1365 - [c63]Yining Wang, Aarti Singh:
Linear Quantization by Effective-Resistance Sampling. ICASSP 2018: 6927-6930 - [c62]Simon S. Du, Jason D. Lee, Yuandong Tian, Aarti Singh, Barnabás Póczos:
Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local Minima. ICML 2018: 1338-1347 - [c61]Yichong Xu, Hariank Muthakana, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski:
Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information. ICML 2018: 5469-5478 - [c60]Simon S. Du, Yining Wang, Xiyu Zhai, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Aarti Singh:
How Many Samples are Needed to Estimate a Convolutional Neural Network? NeurIPS 2018: 371-381 - [c59]Yining Wang, Sivaraman Balakrishnan, Aarti Singh:
Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates. NeurIPS 2018: 4343-4354 - [c58]Sivaraman Balakrishnan, Yo Joong Choe, Aarti Singh, Jean M. Vettel, Timothy D. Verstynen:
Local White Matter Architecture Defines Functional Brain Dynamics. SMC 2018: 595-602 - [i56]Yifan Wu, Barnabás Póczos, Aarti Singh:
Towards Understanding the Generalization Bias of Two Layer Convolutional Linear Classifiers with Gradient Descent. CoRR abs/1802.04420 (2018) - [i55]Siheng Chen, Aarti Singh, Jelena Kovacevic:
Multiresolution Representations for Piecewise-Smooth Signals on Graphs. CoRR abs/1803.02944 (2018) - [i54]Yining Wang, Sivaraman Balakrishnan, Aarti Singh:
Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates. CoRR abs/1803.08586 (2018) - [i53]Simon S. Du, Yining Wang, Xiyu Zhai, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Aarti Singh:
How Many Samples are Needed to Learn a Convolutional Neural Network? CoRR abs/1805.07883 (2018) - [i52]Simon S. Du, Yining Wang, Sivaraman Balakrishnan, Pradeep Ravikumar, Aarti Singh:
Robust Nonparametric Regression under Huber's ε-contamination Model. CoRR abs/1805.10406 (2018) - [i51]Yichong Xu, Hariank Muthakana, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski:
Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information. CoRR abs/1806.03286 (2018) - [i50]Ivan Stelmakh, Nihar B. Shah, Aarti Singh:
PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review. CoRR abs/1806.06237 (2018) - [i49]Simon S. Du, Xiyu Zhai, Barnabás Póczos, Aarti Singh:
Gradient Descent Provably Optimizes Over-parameterized Neural Networks. CoRR abs/1810.02054 (2018) - [i48]Yining Wang, Erva Ulu, Aarti Singh, Levent Burak Kara:
Efficient Load Sampling for Worst-Case Structural Analysis Under Force Location Uncertainty. CoRR abs/1810.10977 (2018) - 2017
- [j13]Dimple Juneja, Aarti Singh, Rashmi Singh, Saurabh Mukherjee:
A Thorough Insight into Theoretical and Practical Developments in MultiAgent Systems. Int. J. Ambient Comput. Intell. 8(1): 23-49 (2017) - [j12]Aarti Singh, Dimple Juneja, Manisha Malhotra:
A novel agent based autonomous and service composition framework for cost optimization of resource provisioning in cloud computing. J. King Saud Univ. Comput. Inf. Sci. 29(1): 19-28 (2017) - [j11]Yining Wang, Adams Wei Yu, Aarti Singh:
On Computationally Tractable Selection of Experiments in Measurement-Constrained Regression Models. J. Mach. Learn. Res. 18: 143:1-143:41 (2017) - [j10]Yining Wang, Aarti Singh:
Provably Correct Algorithms for Matrix Column Subset Selection with Selectively Sampled Data. J. Mach. Learn. Res. 18: 156:1-156:42 (2017) - [j9]Siheng Chen, Yaoqing Yang, Shi Zong, Aarti Singh, Jelena Kovacevic:
Detecting Localized Categorical Attributes on Graphs. IEEE Trans. Signal Process. 65(10): 2725-2740 (2017) - [c57]Sivaraman Balakrishnan, Simon S. Du, Jerry Li, Aarti Singh:
Computationally Efficient Robust Sparse Estimation in High Dimensions. COLT 2017: 169-212 - [c56]Zeyuan Allen-Zhu, Yuanzhi Li, Aarti Singh, Yining Wang:
Near-Optimal Design of Experiments via Regret Minimization. ICML 2017: 126-135 - [c55]Pengtao Xie, Aarti Singh, Eric P. Xing:
Uncorrelation and Evenness: a New Diversity-Promoting Regularizer. ICML 2017: 3811-3820 - [c54]Simon S. Du, Yining Wang, Aarti Singh:
On the Power of Truncated SVD for General High-rank Matrix Estimation Problems. NIPS 2017: 445-455 - [c53]Simon S. Du, Jayanth Koushik, Aarti Singh, Barnabás Póczos:
Hypothesis Transfer Learning via Transformation Functions. NIPS 2017: 574-584 - [c52]Simon S. Du, Chi Jin, Jason D. Lee, Michael I. Jordan, Aarti Singh, Barnabás Póczos:
Gradient Descent Can Take Exponential Time to Escape Saddle Points. NIPS 2017: 1067-1077 - [c51]Yichong Xu, Hongyang Zhang, Aarti Singh, Artur Dubrawski, Kyle Miller:
Noise-Tolerant Interactive Learning Using Pairwise Comparisons. NIPS 2017: 2431-2440 - [e1]Aarti Singh, Xiaojin (Jerry) Zhu:
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, AISTATS 2017, 20-22 April 2017, Fort Lauderdale, FL, USA. Proceedings of Machine Learning Research 54, PMLR 2017 [contents] - [i47]Yining Wang, Jialei Wang, Sivaraman Balakrishnan, Aarti Singh:
Rate Optimal Estimation and Confidence Intervals for High-dimensional Regression with Missing Covariates. CoRR abs/1702.02686 (2017) - [i46]Simon S. Du, Yining Wang, Aarti Singh:
On the Power of Truncated SVD for General High-rank Matrix Estimation Problems. CoRR abs/1702.06861 (2017) - [i45]Simon S. Du, Sivaraman Balakrishnan, Aarti Singh:
Computationally Efficient Robust Estimation of Sparse Functionals. CoRR abs/1702.07709 (2017) - [i44]Simon S. Du, Chi Jin, Jason D. Lee, Michael I. Jordan, Barnabás Póczos, Aarti Singh:
Gradient Descent Can Take Exponential Time to Escape Saddle Points. CoRR abs/1705.10412 (2017) - [i43]Yining Wang, Simon S. Du, Sivaraman Balakrishnan, Aarti Singh:
Stochastic Zeroth-order Optimization in High Dimensions. CoRR abs/1710.10551 (2017) - [i42]Zeyuan Allen-Zhu, Yuanzhi Li, Aarti Singh, Yining Wang:
Near-Optimal Discrete Optimization for Experimental Design: A Regret Minimization Approach. CoRR abs/1711.05174 (2017) - [i41]Simon S. Du, Jason D. Lee, Yuandong Tian, Barnabás Póczos, Aarti Singh:
Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local Minima. CoRR abs/1712.00779 (2017) - 2016
- [j8]Fang-Cheng Yeh, Jean M. Vettel, Aarti Singh, Barnabás Póczos, Scott T. Grafton, Kirk I. Erickson, Wen-Yih Isaac Tseng, Timothy D. Verstynen:
Quantifying Differences and Similarities in Whole-Brain White Matter Architecture Using Local Connectome Fingerprints. PLoS Comput. Biol. 12(11) (2016) - [j7]Wahiba Ben Abdessalem Karaa, Zeineb Ben Azzouz, Aarti Singh, Nilanjan Dey, Amira S. Ashour, Henda Ben Ghézala:
Automatic builder of class diagram (ABCD): an application of UML generation from functional requirements. Softw. Pract. Exp. 46(11): 1443-1458 (2016) - [j6]Siheng Chen, Rohan Varma, Aarti Singh, Jelena Kovacevic:
Signal Recovery on Graphs: Fundamental Limits of Sampling Strategies. IEEE Trans. Signal Inf. Process. over Networks 2(4): 539-554 (2016) - [j5]James Sharpnack, Alessandro Rinaldo, Aarti Singh:
Detecting Anomalous Activity on Networks With the Graph Fourier Scan Statistic. IEEE Trans. Signal Process. 64(2): 364-379 (2016) - [c50]Yining Wang, Aarti Singh:
Noise-Adaptive Margin-Based Active Learning and Lower Bounds under Tsybakov Noise Condition. AAAI 2016: 2180-2186 - [c49]Yining Wang, Yu-Xiang Wang, Aarti Singh:
Graph Connectivity in Noisy Sparse Subspace Clustering. AISTATS 2016: 538-546 - [c48]Gautam Dasarathy, Aarti Singh, Maria-Florina Balcan, Jong Hyuk Park:
Active Learning Algorithms for Graphical Model Selection. AISTATS 2016: 1356-1364 - [c47]Siheng Chen, Yaoqing Yang, Aarti Singh, Jelena Kovacevic:
Signal detection on graphs: Bernoulli noise model. GlobalSIP 2016: 395-399 - [c46]Siheng Chen, Rohan Varma, Aarti Singh, Jelena Kovacevic:
Representations of piecewise smooth signals on graphs. ICASSP 2016: 6370-6374 - [c45]Aarti Singh, Kavita Gupta:
Optimal Cluster Head Election Algorithm for Mobile Wireless Sensor Networks. ICTCS 2016: 132:1-132:6 - [c44]Aaditya Ramdas, David Isenberg, Aarti Singh, Larry A. Wasserman:
Minimax lower bounds for linear independence testing. ISIT 2016: 965-969 - [c43]Siheng Chen, Rohan Varma, Aarti Singh, Jelena Kovacevic:
A statistical perspective of sampling scores for linear regression. ISIT 2016: 1556-1560 - [c42]Bo Li, Yining Wang, Aarti Singh, Yevgeniy Vorobeychik:
Data Poisoning Attacks on Factorization-Based Collaborative Filtering. NIPS 2016: 1885-1893 - [i40]Yining Wang, Aarti Singh:
Minimax Subsampling for Estimation and Prediction in Low-Dimensional Linear Regression. CoRR abs/1601.02068 (2016) - [i39]Aaditya Ramdas, David Isenberg, Aarti Singh, Larry A. Wasserman:
Minimax Lower Bounds for Linear Independence Testing. CoRR abs/1601.06259 (2016) - [i38]Gautam Dasarathy, Aarti Singh, Maria-Florina Balcan, Jong Hyuk Park:
Active Learning Algorithms for Graphical Model Selection. CoRR abs/1602.00354 (2016) - [i37]Aaditya Ramdas, Aarti Singh, Larry A. Wasserman:
Classification Accuracy as a Proxy for Two Sample Testing. CoRR abs/1602.02210 (2016) - [i36]Siheng Chen, Yaoqing Yang, Shi Zong, Aarti Singh, Jelena Kovacevic:
Detecting Structure-correlated Attributes on Graphs. CoRR abs/1604.00657 (2016) - [i35]Bo Li, Yining Wang, Aarti Singh, Yevgeniy Vorobeychik:
Data Poisoning Attacks on Factorization-Based Collaborative Filtering. CoRR abs/1608.08182 (2016) - [i34]Yining Wang, Yu-Xiang Wang, Aarti Singh:
A Theoretical Analysis of Noisy Sparse Subspace Clustering on Dimensionality-Reduced Data. CoRR abs/1610.07650 (2016) - [i33]Simon Shaolei Du, Jayanth Koushik, Aarti Singh, Barnabás Póczos:
Transformation Function Based Methods for Model Shift. CoRR abs/1612.01020 (2016) - 2015
- [j4]Aarti Singh, Manisha Malhotra:
Agent based Resource Allocation Mechanism Focusing Cost Optimization in Cloud Computing. Int. J. Cloud Appl. Comput. 5(3): 53-61 (2015) - [j3]Aarti Singh, Anu Sharma, Nilanjan Dey:
Semantics and Agents Oriented Web Personalization: State of the Art. Int. J. Serv. Sci. Manag. Eng. Technol. 6(2): 35-49 (2015) - [c41]Aaditya Ramdas, Sashank Jakkam Reddi, Barnabás Póczos, Aarti Singh, Larry A. Wasserman:
On the Decreasing Power of Kernel and Distance Based Nonparametric Hypothesis Tests in High Dimensions. AAAI 2015: 3571-3577 - [c40]Martin Azizyan, Aarti Singh, Larry A. Wasserman:
Efficient Sparse Clustering of High-Dimensional Non-spherical Gaussian Mixtures. AISTATS 2015 - [c39]Sashank J. Reddi, Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman:
On the High Dimensional Power of a Linear-Time Two Sample Test under Mean-shift Alternatives. AISTATS 2015 - [c38]Yining Wang, Aarti Singh:
Column Subset Selection with Missing Data via Active Sampling. AISTATS 2015 - [c37]Yining Wang, Aarti Singh:
An empirical comparison of sampling techniques for matrix column subset selection. Allerton 2015: 1069-1074 - [c36]Yining Wang, Yu-Xiang Wang, Aarti Singh:
A Deterministic Analysis of Noisy Sparse Subspace Clustering for Dimensionality-reduced Data. ICML 2015: 1422-1431 - [c35]Yining Wang, Yu-Xiang Wang, Aarti Singh:
Differentially private subspace clustering. NIPS 2015: 1000-1008 - [i32]Yining Wang, Yu-Xiang Wang, Aarti Singh:
Clustering Consistent Sparse Subspace Clustering. CoRR abs/1504.01046 (2015) - [i31]Siheng Chen, Rohan Varma, Aarti Singh, Jelena Kovacevic:
Signal Recovery on Graphs: Random versus Experimentally Designed Sampling. CoRR abs/1504.05427 (2015) - [i30]Martin Azizyan, Yen-Chi Chen, Aarti Singh, Larry A. Wasserman:
Risk Bounds For Mode Clustering. CoRR abs/1505.00482 (2015) - [i29]Aaditya Ramdas, Aarti Singh:
Algorithmic Connections Between Active Learning and Stochastic Convex Optimization. CoRR abs/1505.04214 (2015) - [i28]Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman:
An Analysis of Active Learning With Uniform Feature Noise. CoRR abs/1505.04215 (2015) - [i27]Yining Wang, Aarti Singh:
Provably Correct Active Sampling Algorithms for Matrix Column Subset Selection with Missing Data. CoRR abs/1505.04343 (2015) - [i26]Martin Azizyan, Akshay Krishnamurthy, Aarti Singh:
Extreme Compressive Sampling for Covariance Estimation. CoRR abs/1506.00898 (2015) - [i25]Aaditya Ramdas, Sashank J. Reddi, Barnabás Póczos, Aarti Singh, Larry A. Wasserman:
Adaptivity and Computation-Statistics Tradeoffs for Kernel and Distance based High Dimensional Two Sample Testing. CoRR abs/1508.00655 (2015) - [i24]Siheng Chen, Rohan Varma, Aarti Singh, Jelena Kovacevic:
Signal Recovery on Graphs: Fundamental Limits of Sampling Strategies. CoRR abs/1512.05405 (2015) - [i23]Siheng Chen, Rohan Varma, Aarti Singh, Jelena Kovacevic:
Signal Representations on Graphs: Tools and Applications. CoRR abs/1512.05406 (2015) - 2014
- [c34]Martin Azizyan, Akshay Krishnamurthy, Aarti Singh:
Subspace learning from extremely compressed measurements. ACSSC 2014: 311-315 - [c33]Junier B. Oliva, Barnabás Póczos, Timothy D. Verstynen, Aarti Singh, Jeff G. Schneider, Fang-Cheng Yeh, Wen-Yih Isaac Tseng:
FuSSO: Functional Shrinkage and Selection Operator. AISTATS 2014: 715-723 - [c32]Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman:
An Analysis of Active Learning with Uniform Feature Noise. AISTATS 2014: 805-813 - [i22]Akshay Krishnamurthy, Martin Azizyan, Aarti Singh:
Subspace Learning from Extremely Compressed Measurements. CoRR abs/1404.0751 (2014) - [i21]Sashank J. Reddi, Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman:
Kernel MMD, the Median Heuristic and Distance Correlation in High Dimensions. CoRR abs/1406.2083 (2014) - [i20]Yining Wang, Aarti Singh:
Noise-adaptive Margin-based Active Learning for Multi-dimensional Data. CoRR abs/1406.5383 (2014) - [i19]Akshay Krishnamurthy, Aarti Singh:
On the Power of Adaptivity in Matrix Completion and Approximation. CoRR abs/1407.3619 (2014) - [i18]Aaditya Ramdas, Sashank J. Reddi, Barnabás Póczos, Aarti Singh, Larry A. Wasserman:
On the High-dimensional Power of Linear-time Kernel Two-Sample Testing under Mean-difference Alternatives. CoRR abs/1411.6314 (2014) - 2013
- [c31]Akshay Krishnamurthy, James Sharpnack, Aarti Singh:
Recovering graph-structured activations using adaptive compressive measurements. ACSSC 2013: 765-769 - [c30]Barnabás Póczos, Aarti Singh, Alessandro Rinaldo, Larry A. Wasserman:
Distribution-Free Distribution Regression. AISTATS 2013: 507-515 - [c29]James Sharpnack, Aarti Singh, Akshay Krishnamurthy:
Detecting Activations over Graphs using Spanning Tree Wavelet Bases. AISTATS 2013: 536-544 - [c28]James Sharpnack, Aarti Singh, Alessandro Rinaldo:
Changepoint Detection over Graphs with the Spectral Scan Statistic. AISTATS 2013: 545-553 - [c27]Aaditya Ramdas, Aarti Singh:
Algorithmic Connections between Active Learning and Stochastic Convex Optimization. ALT 2013: 339-353 - [c26]James Sharpnack, Aarti Singh:
Near-optimal and computationally efficient detectors for weak and sparse graph-structured patterns. GlobalSIP 2013: 443-446 - [c25]Aaditya Ramdas, Aarti Singh:
Exploring the intersection of active learning and stochastic convex optimization. GlobalSIP 2013: 1122 - [c24]Aaditya Ramdas, Aarti Singh:
Optimal rates for stochastic convex optimization under Tsybakov noise condition. ICML (1) 2013: 365-373 - [c23]Akshay Krishnamurthy, Aarti Singh:
Low-Rank Matrix and Tensor Completion via Adaptive Sampling. NIPS 2013: 836-844 - [c22]James Sharpnack, Akshay Krishnamurthy, Aarti Singh:
Near-optimal Anomaly Detection in Graphs using Lovasz Extended Scan Statistic. NIPS 2013: 1959-1967 - [c21]Martin Azizyan, Aarti Singh, Larry A. Wasserman:
Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation. NIPS 2013: 2139-2147 - [c20]Sivaraman Balakrishnan, Srivatsan Narayanan, Alessandro Rinaldo, Aarti Singh, Larry A. Wasserman:
Cluster Trees on Manifolds. NIPS 2013: 2679-2687 - [i17]Barnabás Póczos, Alessandro Rinaldo, Aarti Singh, Larry A. Wasserman:
Distribution-Free Distribution Regression. CoRR abs/1302.0082 (2013) - [i16]Sivaraman Balakrishnan, Brittany Fasy, Fabrizio Lecci, Alessandro Rinaldo, Aarti Singh, Larry A. Wasserman:
Statistical Inference For Persistent Homology. CoRR abs/1303.7117 (2013) - [i15]Akshay Krishnamurthy, James Sharpnack, Aarti Singh:
Recovering Graph-Structured Activations using Adaptive Compressive Measurements. CoRR abs/1305.0213 (2013) - [i14]Martin Azizyan, Aarti Singh, Larry A. Wasserman:
Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation. CoRR abs/1306.2035 (2013) - [i13]Sivaraman Balakrishnan, Srivatsan Narayanan, Alessandro Rinaldo, Aarti Singh, Larry A. Wasserman:
Cluster Trees on Manifolds. CoRR abs/1307.6515 (2013) - [i12]Sivaraman Balakrishnan, Alessandro Rinaldo, Aarti Singh, Larry A. Wasserman:
Tight Lower Bounds for Homology Inference. CoRR abs/1307.7666 (2013) - [i11]Frédéric Chazal, Brittany Terese Fasy, Fabrizio Lecci, Alessandro Rinaldo, Aarti Singh, Larry A. Wasserman:
On the Bootstrap for Persistence Diagrams and Landscapes. CoRR abs/1311.0376 (2013) - [i10]Junier B. Oliva, Barnabás Póczos, Timothy D. Verstynen, Aarti Singh, Jeff G. Schneider, Fang-Cheng Yeh, Wen-Yih Isaac Tseng:
FuSSO: Functional Shrinkage and Selection Operator. CoRR abs/1311.2234 (2013) - 2012
- [j2]Alessandro Rinaldo, Aarti Singh, Rebecca Nugent, Larry A. Wasserman:
Stability of density-based clustering. J. Mach. Learn. Res. 13: 905-948 (2012) - [c19]Akshay Krishnamurthy, Sivaraman Balakrishnan, Min Xu, Aarti Singh:
Efficient Active Algorithms for Hierarchical Clustering. ICML 2012 - [c18]Akshay Krishnamurthy, Aarti Singh:
Robust multi-source network tomography using selective probes. INFOCOM 2012: 1629-1637 - [c17]Martin Azizyan, Aarti Singh:
Subspace detection of high-dimensional vectors using compressive sampling. SSP 2012: 724-727 - [c16]Sivaraman Balakrishnan, Alessandro Rinaldo, Don Sheehy, Aarti Singh, Larry A. Wasserman:
Minimax rates for homology inference. AISTATS 2012: 64-72 - [c15]James Sharpnack, Aarti Singh, Alessandro Rinaldo:
Sparsistency of the Edge Lasso over Graphs. AISTATS 2012: 1028-1036 - [i9]Martin Azizyan, Aarti Singh, Larry A. Wasserman:
Density-Sensitive Semisupervised Inference. CoRR abs/1204.1685 (2012) - [i8]James Sharpnack, Alessandro Rinaldo, Aarti Singh:
Changepoint Detection over Graphs with the Spectral Scan Statistic. CoRR abs/1206.0773 (2012) - [i7]Akshay Krishnamurthy, James Sharpnack, Aarti Singh:
Detecting Activations over Graphs using Spanning Tree Wavelet Bases. CoRR abs/1206.0937 (2012) - [i6]Akshay Krishnamurthy, Sivaraman Balakrishnan, Min Xu, Aarti Singh:
Efficient Active Algorithms for Hierarchical Clustering. CoRR abs/1206.4672 (2012) - [i5]Aaditya Ramdas, Aarti Singh:
Optimal Stochastic Convex Optimization Through The Lens Of Active Learning. CoRR abs/1207.3012 (2012) - 2011
- [c14]Aarti Singh, Dimple Juneja, A. K. Sharma:
Design of an Intelligent and Adaptive Mapping Mechanism for Multiagent Interface. HPAGC 2011: 373-384 - [c13]Mladen Kolar, Sivaraman Balakrishnan, Alessandro Rinaldo, Aarti Singh:
Minimax Localization of Structural Information in Large Noisy Matrices. NIPS 2011: 909-917 - [c12]Sivaraman Balakrishnan, Min Xu, Akshay Krishnamurthy, Aarti Singh:
Noise Thresholds for Spectral Clustering. NIPS 2011: 954-962 - [c11]Brian Eriksson, Gautam Dasarathy, Aarti Singh, Robert D. Nowak:
Active Clustering: Robust and Efficient Hierarchical Clustering using Adaptively Selected Similarities. AISTATS 2011: 260-268 - [i4]Brian Eriksson, Gautam Dasarathy, Aarti Singh, Robert D. Nowak:
Active Clustering: Robust and Efficient Hierarchical Clustering using Adaptively Selected Similarities. CoRR abs/1102.3887 (2011) - [i3]Aarti Singh, Dimple Juneja, A. K. Sharma:
Agent Development Toolkits. CoRR abs/1111.5930 (2011) - [i2]Sivaraman Balakrishnan, Alessandro Rinaldo, Don Sheehy, Aarti Singh, Larry A. Wasserman:
Minimax Rates for Homology Inference. CoRR abs/1112.5627 (2011) - 2010
- [c10]James Sharpnack, Aarti Singh:
Identifying graph-structured activation patterns in networks. NIPS 2010: 2137-2145 - [c9]Aarti Singh, Robert D. Nowak, A. Robert Calderbank:
Detecting Weak but Hierarchically-Structured Patterns in Networks. AISTATS 2010: 749-756 - [i1]Aarti Singh, Robert D. Nowak, A. Robert Calderbank:
Detecting Weak but Hierarchically-Structured Patterns in Networks. CoRR abs/1003.0205 (2010)
2000 – 2009
- 2009
- [c8]Andrew B. Goldberg, Xiaojin Zhu, Aarti Singh, Zhiting Xu, Robert D. Nowak:
Multi-Manifold Semi-Supervised Learning. AISTATS 2009: 169-176 - 2008
- [j1]Aarti Singh, Chen Chen, Weiguo Liu, Wayne P. Mitchell, Bertil Schmidt:
A Hybrid Computational Grid Architecture for Comparative Genomics. IEEE Trans. Inf. Technol. Biomed. 12(2): 218-225 (2008) - [c7]Aarti Singh, Robert D. Nowak, Clayton D. Scott:
Adaptive Hausdorff Estimation of Density Level Sets. COLT 2008: 491-502 - [c6]Parameswaran Ramanathan, Aarti Singh:
Delay-Differentiated Gossiping in Delay Tolerant Networks. ICC 2008: 3291-3295 - [c5]Zachary T. Harmany, Rebecca Willett, Aarti Singh, Robert D. Nowak:
Controlling the error in FMRI: Hypothesis testing or set estimation? ISBI 2008: 552-555 - [c4]Aarti Singh, Robert D. Nowak, Xiaojin Zhu:
Unlabeled data: Now it helps, now it doesn't. NIPS 2008: 1513-1520 - 2006
- [c3]Michael G. Rabbat, Jarvis D. Haupt, Aarti Singh, Robert D. Nowak:
Decentralized compression and predistribution via randomized gossiping. IPSN 2006: 51-59 - [c2]Aarti Singh, Robert D. Nowak, Parameswaran Ramanathan:
Active learning for adaptive mobile sensing networks. IPSN 2006: 60-68 - 2005
- [c1]Aarti Singh, Parmesh Ramanathan, Barry D. Van Veen:
Spatial reuse through adaptive interference cancellation in multi-antenna wireless networks. GLOBECOM 2005: 5
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2025-03-22 01:13 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
