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ORCIDBin Yu 0001
Person information
- affiliation: University of California, Berkeley, Department of Statistics, CA, USA
- affiliation: University of Wisconsin at Madison, Department of Statistics, WI, USA
Other persons with the same name
- Bin Yu — disambiguation page
- Bin Yu 0002 — Michigan State University, Department of Computer Science, East Lansing, MI, USA
- Bin Yu 0003
![[0000-0003-1999-7413]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0003-1999-7413")
— Zhengzhou Information Science and Technology Institute, Department of Computer Science, China (and 2 more) - Bin Yu 0004 — Eindhoven University of Technology, Industrial Design Department, The Netherlands
- Bin Yu 0005 — Brunel University London, UK
- Bin Yu 0006 — Carnegie Mellon University, Pittsburgh, PA, USA (and 1 more)
- Bin Yu 0007 — Qingdao University of Science and Technology, College of Mathematics and Physics, China (and 1 more)
- Bin Yu 0008 — Xidian University, School of Computer Science and Technology, Shaanxi, China (and 1 more)
- Bin Yu 0009 — Monash University, DATA61, CSIRO, Melbourne, VIC, Australia
- Bin Yu 0010 — University of Illinois Urbana-Champaign, Department of Computer Science, IL, USA
- Bin Yu 0011 — Xidian University, School of Computer Science and Technology, Xi'an, Shaanxi, China (and 1 more)
- Bin Yu 0012 — Hunan Normal University, School of Mathematics and Statistics, Changsha, China
- Bin Yu 0013 — University of Electronic Science and Technology of China, National Key Laboratory of Science and Technology on Communications, Chengdu, China (and 1 more)
- Bin Yu 0014 — Xidian University, Xi'an, Shaanxi, China
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2020 – today
- 2025
[c59]Yanda Chen, Chandan Singh, Xiaodong Liu, Simiao Zuo, Bin Yu, He He, Jianfeng Gao:
Towards Consistent Natural-Language Explanations via Explanation-Consistency Finetuning. COLING 2025: 7558-7568- 2024
- [j47]James Duncan, Tiffany M. Tang, Corrine F. Elliott, Philippe Boileau, Bin Yu:
simChef: High-quality data science simulations in R. J. Open Source Softw. 9(96): 6156 (2024) - [c58]Andy Zhou, Xiaojun Xu, Ramesh Raghunathan, Alok Lal, Xinze Guan, Bin Yu, Bo Li:
KnowGraph: Knowledge-Enabled Anomaly Detection via Logical Reasoning on Graph Data. CCS 2024: 168-182 - [c57]Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Briton Park, Tristan Naumann, Anobel Y. Odisho, Bin Yu:
Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making. ICLR 2024 - [c56]Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao:
Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs. ICLR 2024 - [c55]Soufiane Hayou, Nikhil Ghosh, Bin Yu:
LoRA+: Efficient Low Rank Adaptation of Large Models. ICML 2024 - [c54]Aaron Jiaxun Li, Robin Netzorg, Zhihan Cheng, Zhuoqin Zhang, Bin Yu:
Improving Prototypical Visual Explanations with Reward Reweighing, Reselection, and Retraining. ICML 2024 - [c53]Neil Mallinar, Austin Zane, Spencer Frei, Bin Yu:
Minimum-Norm Interpolation Under Covariate Shift. ICML 2024 - [c52]Liwen Sun, Abhineet Agarwal, Aaron Kornblith, Bin Yu, Chenyan Xiong:
ED-Copilot: Reduce Emergency Department Wait Time with Language Model Diagnostic Assistance. ICML 2024 - [c51]Soufiane Hayou, Nikhil Ghosh, Bin Yu:
The Impact of Initialization on LoRA Finetuning Dynamics. NeurIPS 2024 - [i60]Yanda Chen, Chandan Singh, Xiaodong Liu, Simiao Zuo, Bin Yu, He He, Jianfeng Gao:
Towards Consistent Natural-Language Explanations via Explanation-Consistency Finetuning. CoRR abs/2401.13986 (2024) - [i59]Soufiane Hayou, Nikhil Ghosh, Bin Yu:
LoRA+: Efficient Low Rank Adaptation of Large Models. CoRR abs/2402.12354 (2024) - [i58]Neil Mallinar, Austin Zane, Spencer Frei, Bin Yu:
Minimum-Norm Interpolation Under Covariate Shift. CoRR abs/2404.00522 (2024) - [i57]Soufiane Hayou, Nikhil Ghosh, Bin Yu:
The Impact of Initialization on LoRA Finetuning Dynamics. CoRR abs/2406.08447 (2024) - [i56]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) - [i55]Yan Shuo Tan, Omer Ronen, Theo Saarinen, Bin Yu:
The Computational Curse of Big Data for Bayesian Additive Regression Trees: A Hitting Time Analysis. CoRR abs/2406.19958 (2024) - [i54]Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Anobel Y. Odisho, Peter R. Carroll, Bin Yu:
Mechanistic Interpretation through Contextual Decomposition in Transformers. CoRR abs/2407.00886 (2024) - [i53]Richard Antonello, Chandan Singh, Shailee Jain, Aliyah R. Hsu, Jianfeng Gao, Bin Yu, Alexander Huth:
A generative framework to bridge data-driven models and scientific theories in language neuroscience. CoRR abs/2410.00812 (2024) - [i52]Andy Zhou, Xiaojun Xu, Ramesh Raghunathan, Alok Lal, Xinze Guan, Bin Yu, Bo Li:
KnowGraph: Knowledge-Enabled Anomaly Detection via Logical Reasoning on Graph Data. CoRR abs/2410.08390 (2024) - 2023
- [j46]Raaz Dwivedi, Chandan Singh, Bin Yu, Martin J. Wainwright:
Revisiting minimum description length complexity in overparameterized models. J. Mach. Learn. Res. 24: 268:1-268:59 (2023) - [c50]Liyuan Liu, Chengyu Dong, Xiaodong Liu, Bin Yu, Jianfeng Gao:
Bridging Discrete and Backpropagation: Straight-Through and Beyond. NeurIPS 2023 - [i51]Liyuan Liu, Chengyu Dong, Xiaodong Liu, Bin Yu, Jianfeng Gao:
Bridging Discrete and Backpropagation: Straight-Through and Beyond. CoRR abs/2304.08612 (2023) - [i50]Chandan Singh, Aliyah R. Hsu, Richard Antonello, Shailee Jain, Alexander G. Huth, Bin Yu, Jianfeng Gao:
Explaining black box text modules in natural language with language models. CoRR abs/2305.09863 (2023) - [i49]Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Briton Park, Tristan Naumann, Anobel Y. Odisho, Bin Yu:
An Investigation into the Effects of Pre-training Data Distributions for Pathology Report Classification. CoRR abs/2305.17588 (2023) - [i48]Abhineet Agarwal, Ana M. Kenney, Yan Shuo Tan, Tiffany M. Tang, Bin Yu:
MDI+: A Flexible Random Forest-Based Feature Importance Framework. CoRR abs/2307.01932 (2023) - [i47]Robin Netzorg, Jiaxun Li, Bin Yu:
Improving Prototypical Part Networks with Reward Reweighing, Reselection, and Retraining. CoRR abs/2307.03887 (2023) - [i46]Nikhil Ghosh, Spencer Frei, Wooseok Ha, Bin Yu:
The Effect of SGD Batch Size on Autoencoder Learning: Sparsity, Sharpness, and Feature Learning. CoRR abs/2308.03215 (2023) - [i45]Keru Wu, Yuansi Chen, Wooseok Ha, Bin Yu:
Prominent Roles of Conditionally Invariant Components in Domain Adaptation: Theory and Algorithms. CoRR abs/2309.10301 (2023) - [i44]Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao:
Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs. CoRR abs/2311.02262 (2023) - 2022
- [j45]James Duncan, Rush Kapoor, Abhineet Agarwal, Chandan Singh, Bin Yu:
VeridicalFlow: a Python package for building trustworthy data science pipelines with PCS. J. Open Source Softw. 7(69): 3895 (2022) - [j44]Dino Oglic, Zoran Cvetkovic, Peter Sollich, Steve Renals, Bin Yu:
Towards Robust Waveform-Based Acoustic Models. IEEE ACM Trans. Audio Speech Lang. Process. 30: 1977-1992 (2022) - [c49]Yan Shuo Tan, Abhineet Agarwal, Bin Yu:
A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds. AISTATS 2022: 9663-9685 - [c48]Nikhil Ghosh, Song Mei, Bin Yu:
The Three Stages of Learning Dynamics in High-dimensional Kernel Methods. ICLR 2022 - [c47]Abhineet Agarwal, Yan Shuo Tan, Omer Ronen, Chandan Singh, Bin Yu:
Hierarchical Shrinkage: Improving the accuracy and interpretability of tree-based models. ICML 2022: 111-135 - [i43]Yan Shuo Tan, Chandan Singh, Keyan Nasseri, Abhineet Agarwal, Bin Yu:
Fast Interpretable Greedy-Tree Sums (FIGS). CoRR abs/2201.11931 (2022) - [i42]Abhineet Agarwal, Yan Shuo Tan, Omer Ronen, Chandan Singh, Bin Yu:
Hierarchical Shrinkage: improving the accuracy and interpretability of tree-based methods. CoRR abs/2202.00858 (2022) - [i41]Keyan Nasseri, Chandan Singh, James Duncan, Aaron Kornblith, Bin Yu:
Group Probability-Weighted Tree Sums for Interpretable Modeling of Heterogeneous Data. CoRR abs/2205.15135 (2022) - [i40]Omer Ronen, Theo Saarinen, Yan Shuo Tan, James Duncan, Bin Yu:
A Mixing Time Lower Bound for a Simplified Version of BART. CoRR abs/2210.09352 (2022) - 2021
- [j43]Reza Abbasi-Asl, Bin Yu:
Structural Compression of Convolutional Neural Networks with Applications in Interpretability. Frontiers Big Data 4: 704182 (2021) - [j42]Nicholas Altieri, Briton Park, Mara Olson, John DeNero, Anobel Y. Odisho, Bin Yu:
Supervised line attention for tumor attribute classification from pathology reports: Higher performance with less data. J. Biomed. Informatics 122: 103872 (2021) - [j41]Chandan Singh, Keyan Nasseri, Yan Shuo Tan, Tiffany M. Tang, Bin Yu:
imodels: a python package for fitting interpretable models. J. Open Source Softw. 6(61): 3192 (2021) - [c46]Wooseok Ha, Chandan Singh, François Lanusse, Srigokul Upadhyayula, Bin Yu:
Adaptive wavelet distillation from neural networks through interpretations. NeurIPS 2021: 20669-20682 - [i39]Wooseok Ha, Chandan Singh, François Lanusse, Eli Song, Song Dang, Kangmin He, Srigokul Upadhyayula, Bin Yu:
Adaptive wavelet distillation from neural networks through interpretations. CoRR abs/2107.09145 (2021) - [i38]Chandan Singh, Wooseok Ha, Bin Yu:
Interpreting and improving deep-learning models with reality checks. CoRR abs/2108.06847 (2021) - [i37]Dino Oglic, Zoran Cvetkovic, Peter Sollich, Steve Renals, Bin Yu:
Towards Robust Waveform-Based Acoustic Models. CoRR abs/2110.08634 (2021) - [i36]Yan Shuo Tan, Abhineet Agarwal, Bin Yu:
A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds. CoRR abs/2110.09626 (2021) - [i35]Nikhil Ghosh, Song Mei, Bin Yu:
The Three Stages of Learning Dynamics in High-Dimensional Kernel Methods. CoRR abs/2111.07167 (2021) - 2020
- [j40]Yu Wang, Siqi Wu, Bin Yu:
Unique Sharp Local Minimum in L1-minimization Complete Dictionary Learning. J. Mach. Learn. Res. 21: 63:1-63:52 (2020) - [j39]Yuansi Chen, Raaz Dwivedi, Martin J. Wainwright, Bin Yu:
Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients. J. Mach. Learn. Res. 21: 92:1-92:72 (2020) - [c45]Raaz Dwivedi, Nhat Ho, Koulik Khamaru, Martin J. Wainwright, Michael I. Jordan, Bin Yu:
Sharp Analysis of Expectation-Maximization for Weakly Identifiable Models. AISTATS 2020: 1866-1876 - [c44]Chandan Singh, Wooseok Ha, Bin Yu:
Interpreting and Improving Deep-Learning Models with Reality Checks. xxAI@ICML 2020: 229-254 - [c43]Laura Rieger, Chandan Singh, W. James Murdoch, Bin Yu:
Interpretations are Useful: Penalizing Explanations to Align Neural Networks with Prior Knowledge. ICML 2020: 8116-8126 - [c42]Bin Yu:
Veridical Data Science. WSDM 2020: 4-5 - [i34]Chandan Singh, Wooseok Ha, François Lanusse, Vanessa Böhm, Jia Liu, Bin Yu:
Transformation Importance with Applications to Cosmology. CoRR abs/2003.01926 (2020) - [i33]Nick Altieri, Rebecca L. Barter, James Duncan, Raaz Dwivedi, Karl Kumbier, Xiao Li, Robert Netzorg, Briton Park, Chandan Singh, Yan Shuo Tan, Tiffany M. Tang, Yu Wang, Bin Yu:
Curating a COVID-19 data repository and forecasting county-level death counts in the United States. CoRR abs/2005.07882 (2020) - [i32]Nhat Ho, Koulik Khamaru, Raaz Dwivedi, Martin J. Wainwright, Michael I. Jordan, Bin Yu:
Instability, Computational Efficiency and Statistical Accuracy. CoRR abs/2005.11411 (2020) - [i31]Raaz Dwivedi, Chandan Singh, Bin Yu, Martin J. Wainwright:
Revisiting complexity and the bias-variance tradeoff. CoRR abs/2006.10189 (2020) - [i30]Raaz Dwivedi, Yan Shuo Tan, Briton Park, Mian Wei, Kevin Horgan, David Madigan, Bin Yu:
Stable discovery of interpretable subgroups via calibration in causal studies. CoRR abs/2008.10109 (2020) - [i29]Nick Altieri, Briton Park, Mara Olson, John DeNero, Anobel Y. Odisho, Bin Yu:
Enriched Annotations for Tumor Attribute Classification from Pathology Reports with Limited Labeled Data. CoRR abs/2012.08113 (2020)
2010 – 2019
- 2019
- [j38]Raaz Dwivedi, Yuansi Chen, Martin J. Wainwright, Bin Yu:
Log-concave sampling: Metropolis-Hastings algorithms are fast. J. Mach. Learn. Res. 20: 183:1-183:42 (2019) - [c41]Chandan Singh, W. James Murdoch, Bin Yu:
Hierarchical interpretations for neural network predictions. ICLR (Poster) 2019 - [c40]Xiao Li, Yu Wang, Sumanta Basu, Karl Kumbier, Bin Yu:
A Debiased MDI Feature Importance Measure for Random Forests. NeurIPS 2019: 8047-8057 - [i28]W. James Murdoch, Chandan Singh, Karl Kumbier, Reza Abbasi-Asl, Bin Yu:
Interpretable machine learning: definitions, methods, and applications. CoRR abs/1901.04592 (2019) - [i27]Bin Yu, Karl Kumbier:
Three principles of data science: predictability, computability, and stability (PCS). CoRR abs/1901.08152 (2019) - [i26]Raaz Dwivedi, Nhat Ho, Koulik Khamaru, Martin J. Wainwright, Michael I. Jordan, Bin Yu:
Challenges with EM in application to weakly identifiable mixture models. CoRR abs/1902.00194 (2019) - [i25]Yu Wang, Siqi Wu, Bin Yu:
Unique Sharp Local Minimum in $\ell_1$-minimization Complete Dictionary Learning. CoRR abs/1902.08380 (2019) - [i24]Summer Devlin, Chandan Singh, W. James Murdoch, Bin Yu:
Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees. CoRR abs/1905.07631 (2019) - [i23]Yuansi Chen, Raaz Dwivedi, Martin J. Wainwright, Bin Yu:
Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients. CoRR abs/1905.12247 (2019) - [i22]Xiao Li, Yu Wang, Sumanta Basu, Karl Kumbier, Bin Yu:
A Debiased MDI Feature Importance Measure for Random Forests. CoRR abs/1906.10845 (2019) - [i21]Laura Rieger, Chandan Singh, W. James Murdoch, Bin Yu:
Interpretations are useful: penalizing explanations to align neural networks with prior knowledge. CoRR abs/1909.13584 (2019) - 2018
- [j37]Yuansi Chen, Raaz Dwivedi, Martin J. Wainwright, Bin Yu:
Fast MCMC Sampling Algorithms on Polytopes. J. Mach. Learn. Res. 19: 55:1-55:86 (2018) - [j36]Sumanta Basu, Karl Kumbier, James B. Brown, Bin Yu:
iRF: extracting interactions from random forests. J. Open Source Softw. 3(32): 1077 (2018) - [j35]Bin Yu, Karl Kumbier:
Artificial intelligence and statistics. Frontiers Inf. Technol. Electron. Eng. 19(1): 6-9 (2018) - [c39]Bin Yu:
Three principles of data science: predictability, computability, and stability (PCS). IEEE BigData 2018: 4 - [c38]Raaz Dwivedi, Yuansi Chen, Martin J. Wainwright, Bin Yu:
Log-concave sampling: Metropolis-Hastings algorithms are fast! COLT 2018: 793-797 - [c37]W. James Murdoch, Peter J. Liu, Bin Yu:
Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs. ICLR 2018 - [i20]W. James Murdoch, Peter J. Liu, Bin Yu:
Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs. CoRR abs/1801.05453 (2018) - [i19]Yuansi Chen, Chi Jin, Bin Yu:
Stability and Convergence Trade-off of Iterative Optimization Algorithms. CoRR abs/1804.01619 (2018) - [i18]Chandan Singh, W. James Murdoch, Bin Yu:
Hierarchical interpretations for neural network predictions. CoRR abs/1806.05337 (2018) - [i17]Karl Kumbier, Sumanta Basu, James B. Brown, Susan Celniker, Bin Yu:
Refining interaction search through signed iterative Random Forests. CoRR abs/1810.07287 (2018) - 2017
- [c36]Yuansi Chen, Raaz Dwivedi, Martin J. Wainwright, Bin Yu:
Vaidya walk: A sampling algorithm based on the volumetric barrier. Allerton 2017: 1220-1227 - [c35]Bin Yu:
Three Principles of Data Science: Predictability, Stability and Computability. KDD 2017: 5 - [i16]Reza Abbasi-Asl, Bin Yu:
Structural Compression of Convolutional Neural Networks Based on Greedy Filter Pruning. CoRR abs/1705.07356 (2017) - [i15]Reza Abbasi-Asl, Bin Yu:
Interpreting Convolutional Neural Networks Through Compression. CoRR abs/1711.02329 (2017) - [i14]Bin Yu, Karl Kumbier:
Artificial Intelligence and Statistics. CoRR abs/1712.03779 (2017) - 2016
- [j34]Robert E. Kass, Brian S. Caffo, Marie Davidian, Xiao-Li Meng, Bin Yu, Nancy Reid:
Ten Simple Rules for Effective Statistical Practice. PLoS Comput. Biol. 12(6) (2016) - [c34]Reza Abbasi-Asl, Cengiz Pehlevan, Bin Yu, Dmitri B. Chklovskii:
Do retinal ganglion cells project natural scenes to their principal subspace and whiten them? ACSSC 2016: 1641-1645 - [c33]Adam E. Bloniarz, Ameet Talwalkar, Bin Yu, Christopher Wu:
Supervised Neighborhoods for Distributed Nonparametric Regression. AISTATS 2016: 1450-1459 - [c32]Yang Zhang, Fangzhou Xu, Erwin Frise, Siqi Wu, Bin Yu, Wei Xu:
DataLab: a version data management and analytics system. BIGDSE@ICSE 2016: 12-18 - [i13]Yangbo He, Bin Yu:
Formulas for Counting the Sizes of Markov Equivalence Classes of Directed Acyclic Graphs. CoRR abs/1610.07921 (2016) - 2015
- [j33]Ping Ma, Michael W. Mahoney, Bin Yu:
A statistical perspective on algorithmic leveraging. J. Mach. Learn. Res. 16: 861-911 (2015) - [j32]Yangbo He, Jinzhu Jia, Bin Yu:
Counting and exploring sizes of Markov equivalence classes of directed acyclic graphs. J. Mach. Learn. Res. 16: 2589-2609 (2015) - 2014
- [j31]Garvesh Raskutti, Martin J. Wainwright, Bin Yu:
Early stopping and non-parametric regression: an optimal data-dependent stopping rule. J. Mach. Learn. Res. 15(1): 335-366 (2014) - [c31]Ping Ma, Michael W. Mahoney, Bin Yu:
A Statistical Perspective on Algorithmic Leveraging. ICML 2014: 91-99 - [c30]Antony Joseph, Bin Yu:
Impact of regularization on spectral clustering. ITA 2014: 1-2 - [c29]Adam E. Bloniarz, Ameet Talwalkar, Jonathan Terhorst, Michael I. Jordan, David A. Patterson, Bin Yu, Yun S. Song:
Changepoint Analysis for Efficient Variant Calling. RECOMB 2014: 20-34 - [i12]Jinzhu Jia, Luke Miratrix, Bin Yu, Brian Gawalt, Laurent El Ghaoui, Luke Barnesmoore, Sophie Clavier:
Concise comparative summaries (CCS) of large text corpora with a human experiment. CoRR abs/1404.7362 (2014) - [i11]Sivaraman Balakrishnan, Martin J. Wainwright, Bin Yu:
Statistical guarantees for the EM algorithm: From population to sample-based analysis. CoRR abs/1408.2156 (2014) - [i10]Hongwei Li, Bin Yu:
Error Rate Bounds and Iterative Weighted Majority Voting for Crowdsourcing. CoRR abs/1411.4086 (2014) - 2013
- [j30]Julien Mairal, Bin Yu:
Supervised feature selection in graphs with path coding penalties and network flows. J. Mach. Learn. Res. 14(1): 2449-2485 (2013) - [i9]Ping Ma, Michael W. Mahoney, Bin Yu:
A Statistical Perspective on Algorithmic Leveraging. CoRR abs/1306.5362 (2013) - [i8]Hongwei Li, Bin Yu, Dengyong Zhou:
Error Rate Bounds in Crowdsourcing Models. CoRR abs/1307.2674 (2013) - 2012
- [j29]Garvesh Raskutti, Martin J. Wainwright, Bin Yu:
Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming. J. Mach. Learn. Res. 13: 389-427 (2012) - [c28]Julien Mairal, Bin Yu:
Complexity Analysis of the Lasso Regularization Path. ICML 2012 - [c27]Yanfeng Gu, Shizhe Wang, Tao Shi, Yinghui Lu, Eugene E. Clothiaux, Bin Yu:
Multiple-kernel learning-based unmixing algorithm for estimation of cloud fractions with MODIS and CloudSat data. IGARSS 2012: 1785-1788 - [i7]Julien Mairal, Bin Yu:
Supervised Feature Selection in Graphs with Path Coding Penalties and Network Flows. CoRR abs/1204.4539 (2012) - [i6]Julien Mairal, Bin Yu:
Complexity Analysis of the Lasso Regularization Path. CoRR abs/1205.0079 (2012) - [i5]Yangbo He, Jinzhu Jia, Bin Yu:
Reversible MCMC on Markov equivalence classes of sparse directed acyclic graphs. CoRR abs/1209.5860 (2012) - 2011
- [j28]Shamim N. Pakzad, Guilherme V. Rocha, Bin Yu:
Distributed modal identification using restricted auto regressive models. Int. J. Syst. Sci. 42(9): 1473-1489 (2011) - [j27]Alexandre d'Aspremont, Francis R. Bach, Inderjit S. Dhillon, Bin Yu:
Preface. Math. Program. 127(1): 1-2 (2011) - [j26]Jibran Yousafzai, Peter Sollich, Zoran Cvetkovic, Bin Yu:
Combined Features and Kernel Design for Noise Robust Phoneme Classification Using Support Vector Machines. IEEE Trans. Speech Audio Process. 19(5): 1396-1407 (2011) - [j25]Garvesh Raskutti, Martin J. Wainwright, Bin Yu:
Minimax Rates of Estimation for High-Dimensional Linear Regression Over q -Balls. IEEE Trans. Inf. Theory 57(10): 6976-6994 (2011) - [c26]Garvesh Raskutti, Martin J. Wainwright, Bin Yu:
Early stopping for non-parametric regression: An optimal data-dependent stopping rule. Allerton 2011: 1318-1325 - [c25]Xinyu Dai, Jinzhu Jia, Laurent El Ghaoui, Bin Yu:
SBA-term: Sparse Bilingual Association for Terms. ICSC 2011: 189-192 - 2010
- [j24]Garvesh Raskutti, Martin J. Wainwright, Bin Yu:
Restricted Eigenvalue Properties for Correlated Gaussian Designs. J. Mach. Learn. Res. 11: 2241-2259 (2010) - [c24]Yahong Han, Fei Wu, Jinzhu Jia, Yueting Zhuang, Bin Yu:
Multi-Task Sparse Discriminant Analysis (MtSDA) with Overlapping Categories. AAAI 2010: 469-474 - [c23]Brian Gawalt, Jinzhu Jia, Luke Miratrix, Laurent El Ghaoui, Bin Yu, Sophie Clavier:
Discovering word associations in news media via feature selection and sparse classification. Multimedia Information Retrieval 2010: 211-220 - [c22]Ling Huang, Jinzhu Jia, Bin Yu, Byung-Gon Chun, Petros Maniatis, Mayur Naik:
Predicting Execution Time of Computer Programs Using Sparse Polynomial Regression. NIPS 2010: 883-891 - [i4]Garvesh Raskutti, Martin J. Wainwright, Bin Yu:
Minimax-optimal rates for sparse additive models over kernel classes via convex programming. CoRR abs/1008.3654 (2010) - [i3]Sahand N. Negahban, Pradeep Ravikumar, Martin J. Wainwright, Bin Yu:
A unified framework for high-dimensional analysis of $M$-estimators with decomposable regularizers. CoRR abs/1010.2731 (2010)
2000 – 2009
- 2009
- [j23]Vincent Q. Vu, Bin Yu, Robert E. Kass:
Information in the Nonstationary Case. Neural Comput. 21(3): 688-703 (2009) - [c21]Garvesh Raskutti, Martin J. Wainwright, Bin Yu:
Minimax rates of convergence for high-dimensional regression under ℓq-ball sparsity. Allerton 2009: 251-257 - [c20]Vincent Q. Vu, Bin Yu, Robert E. Kass:
Some statistical issues in estimating information in neural spike trains. ICASSP 2009: 3509-3512 - [c19]Sahand N. Negahban, Pradeep Ravikumar, Martin J. Wainwright, Bin Yu:
A unified framework for high-dimensional analysis of $M$-estimators with decomposable regularizers. NIPS 2009: 1348-1356 - [c18]Garvesh Raskutti, Martin J. Wainwright, Bin Yu:
Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothness. NIPS 2009: 1563-1570 - [i2]Garvesh Raskutti, Martin J. Wainwright, Bin Yu:
Minimax rates of estimation for high-dimensional linear regression over $\ell_q$-balls. CoRR abs/0910.2042 (2009) - 2008
- [c17]Matthew Ager, Zoran Cvetkovic, Peter Sollich, Bin Yu:
Towards robust phoneme classification: Augmentation of PLP models with acoustic waveforms. EUSIPCO 2008: 1-5 - [c16]Jibran Yousafzai, Zoran Cvetkovic, Peter Sollich, Bin Yu:
Combined PLP - Acoustic waveform classification for robust phoneme recognition using support vector machines. EUSIPCO 2008: 1-5 - [c15]Tao Shi, Mikhail Belkin, Bin Yu:
Data spectroscopy: learning mixture models using eigenspaces of convolution operators. ICML 2008: 936-943 - [c14]Pradeep Ravikumar, Garvesh Raskutti, Martin J. Wainwright, Bin Yu:
Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of l1-regularized MLE. NIPS 2008: 1329-1336 - [c13]Pradeep Ravikumar, Vincent Q. Vu, Bin Yu, Thomas Naselaris, Kendrick N. Kay, Jack L. Gallant:
Nonparametric sparse hierarchical models describe V1 fMRI responses to natural images. NIPS 2008: 1337-1344 - [i1]Vincent Q. Vu, Bin Yu, Robert E. Kass:
Information In The Non-Stationary Case. CoRR abs/0806.3978 (2008) - 2007
- [j22]Peng Zhao, Bin Yu:
Stagewise Lasso. J. Mach. Learn. Res. 8: 2701-2726 (2007) - [j21]Bin Yu:
Embracing Statistical Challenges in the Information Technology Age. Technometrics 49(3): 237-248 (2007) - 2006
- [j20]Peter Bühlmann, Bin Yu:
Sparse Boosting. J. Mach. Learn. Res. 7: 1001-1024 (2006) - [j19]Peng Zhao, Bin Yu:
On Model Selection Consistency of Lasso. J. Mach. Learn. Res. 7: 2541-2563 (2006) - [j18]Gang Liang, Nina Taft, Bin Yu:
A fast lightweight approach to origin-destination IP traffic estimation using partial measurements. IEEE Trans. Inf. Theory 52(6): 2634-2648 (2006) - [c12]Jianfeng Gao, Hisami Suzuki, Bin Yu:
Approximation Lasso Methods for Language Modeling. ACL 2006 - 2004
- [j17]Meir Feder, Mário A. T. Figueiredo, Alfred O. Hero III, Chin-Hui Lee, Hans-Andrea Loeliger, Robert D. Nowak, Andrew C. Singer, Bin Yu:
Guest Editorial: Special Issue on Machine Learning Methods in Signal Processing. IEEE Trans. Signal Process. 52(8): 2152 (2004) - [c11]Gang Liang, Bin Yu, Nina Taft:
Maximum entropy models: convergence rates and applications in dynamic system monitoring. ISIT 2004: 168 - 2003
- [j16]Rebecka Jörnsten, Bin Yu:
Simultaneous Gene Clustering and Subset Selection for Sample Classification Via MDL. Bioinform. 19(9): 1100-1109 (2003) - [j15]Rebecka Jörnsten, Wei Wang, Bin Yu, Kannan Ramchandran:
Microarray image compression: SLOCO and the effect of information loss. Signal Process. 83(4): 859-869 (2003) - [j14]Gang Liang, Bin Yu:
Maximum pseudo likelihood estimation in network tomography. IEEE Trans. Signal Process. 51(8): 2043-2053 (2003) - [c10]Tong Zhang, Bin Yu:
On the Convergence of Boosting Procedures. ICML 2003: 904-911 - [c9]Gang Liang, Bin Yu:
Pseudo Likelihood Estimation in Network Tomography. INFOCOM 2003: 2101-2111 - 2002
- [j13]Mark Coates, Alfred O. Hero III, Robert D. Nowak, Bin Yu:
Internet tomography. IEEE Signal Process. Mag. 19(3): 47-65 (2002) - [j12]Gerald Schuller, Bin Yu, Dawei Huang, Bernd Edler:
Perceptual audio coding using adaptive pre- and post-filters and lossless compression. IEEE Trans. Speech Audio Process. 10(6): 379-390 (2002) - [c8]Rebecka Jörnsten, Bin Yu, Wei Wang, Kannan Ramchandran:
Compression of cDNA and inkjet microarray images. ICIP (3) 2002: 961-964 - [c7]Rebecka Jörnsten, Bin Yu:
Compression of cDNA microarray images. ISBI 2002: 38-41 - 2001
- [c6]Sean Dorward, Dawei Huang, Serap A. Savari, Gerald Schuller, Bin Yu:
Low Delay Perpetually Lossless Coding of Audio Signals. Data Compression Conference 2001: 312- - [c5]Gerald Schuller, Bin Yu, Dawei Huang:
Lossless coding of audio signals using cascaded prediction. ICASSP 2001: 3273-3276 - 2000
- [j11]S. Grace Chang, Bin Yu, Martin Vetterli:
Spatially adaptive wavelet thresholding with context modeling for image denoising. IEEE Trans. Image Process. 9(9): 1522-1531 (2000) - [j10]S. Grace Chang, Bin Yu, Martin Vetterli:
Adaptive wavelet thresholding for image denoising and compression. IEEE Trans. Image Process. 9(9): 1532-1546 (2000) - [j9]S. Grace Chang, Bin Yu, Martin Vetterli:
Wavelet thresholding for multiple noisy image copies. IEEE Trans. Image Process. 9(9): 1631-1635 (2000) - [j8]Mark Hansen, Bin Yu:
Wavelet thresholding via MDL for natural images. IEEE Trans. Inf. Theory 46(5): 1778-1788 (2000) - [j7]Lei Li, Bin Yu:
Iterated logarithmic expansions of the pathwise code lengths for exponential families. IEEE Trans. Inf. Theory 46(7): 2683-2689 (2000)
1990 – 1999
- 1999
- [j6]Bin Yu, Michael Ostland, Peng Gong, Ruiliang Pu:
Penalized discriminant analysis of in situ hyperspectral data for conifer species recognition. IEEE Trans. Geosci. Remote. Sens. 37(5): 2569-2577 (1999) - [j5]Youngjun Yoo, Antonio Ortega, Bin Yu:
Image subband coding using context-based classification and adaptive quantization. IEEE Trans. Image Process. 8(12): 1702-1715 (1999) - 1998
- [j4]Andrew R. Barron, Jorma Rissanen, Bin Yu:
The Minimum Description Length Principle in Coding and Modeling. IEEE Trans. Inf. Theory 44(6): 2743-2760 (1998) - [c4]S. Grace Chang, Bin Yu, Martin Vetterli:
Spatially Adaptive Wavelet Thresholding with Context Modeling for Image Denoising. ICIP (1) 1998: 535-539 - [c3]S. Grace Chang, Bin Yu, Martin Vetterli:
Multiple Copy Image Denoising via Wavelet Thresholding. ICIP (1) 1998: 545-549 - 1997
- [c2]S. Grace Chang, Bin Yu, Martin Vetterli:
Image Denoising via Lossy Compression and Wavelet Thresholding. ICIP (1) 1997: 604-607 - 1996
- [j3]Bin Yu:
Lower Bounds on Expected Redundancy for Nonparametric Classes. IEEE Trans. Inf. Theory 42(1): 272-275 (1996) - [c1]Youngjun Yoo, Antonio Ortega, Bin Yu:
Adaptive quantization of image subbands with efficient overhead rate selection. ICIP (2) 1996: 361-364 - 1993
- [j2]Bin Yu, Terry P. Speed:
A rate of convergence result for a universal D-semifaithful code. IEEE Trans. Inf. Theory 39(3): 813-820 (1993) - 1992
- [j1]Jorma Rissanen, Terry P. Speed, Bin Yu:
Density estimation by stochastic complexity. IEEE Trans. Inf. Theory 38(2): 315-323 (1992)
Coauthor Index
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