Bin Yu

182 papers A* 26A 4B 4C 1Misc 4Journal 120Unranked 23
YearRankTypeTitle / Venue / Authors
2025 J jnl
CDR-Agent: Intelligent Selection and Execution of Clinical Decision Rules Using Large Language Model Agents.
CoRR
Zhen Xiang, Aliyah R. Hsu, Austin Zane, Aaron Kornblith, Margaret J. Lin-Martore, Jasmanpreet C. Kaur, Vasuda M. Dokiparthi, Bo Li, Bin Yu
2025 A* conf
Efficient Automated Circuit Discovery in Transformers using Contextual Decomposition.
ICLR
Aliyah R. Hsu, Georgia Zhou, Yeshwanth Cherapanamjeri, Yaxuan Huang, Anobel Y. Odisho, Peter R. Carroll, Bin Yu
2025 J jnl
Enhancing CBMs Through Binary Distillation with Applications to Test-Time Intervention.
CoRR
Matthew Shen, Aliyah R. Hsu, Abhineet Agarwal, Bin Yu
2025 J jnl
Instability, Computational Efficiency and Statistical Accuracy.
J. Mach. Learn. Res.
Nhat Ho, Koulik Khamaru, Raaz Dwivedi, Martin J. Wainwright, Michael I. Jordan, Bin Yu
2025 J jnl
Local MDI+: Local Feature Importances for Tree-Based Models.
CoRR
Zhongyuan Liang, Zachary T. Rewolinski, Abhineet Agarwal, Tiffany M. Tang, Bin Yu
2025 A* conf
Mitigating over-Exploration in Latent Space Optimization using les.
ICML
Omer Ronen, Ahmed Imtiaz Humayun, Richard G. Baraniuk, Randall Balestriero, Bin Yu
2025 J jnl
PCS-UQ: Uncertainty Quantification via the Predictability-Computability-Stability Framework.
CoRR
Abhineet Agarwal, Michael Xiao, Rebecca L. Barter, Omer Ronen, Boyu Fan, Bin Yu
2025 J jnl
PLoP: Precise LoRA Placement for Efficient Finetuning of Large Models.
CoRR
Soufiane Hayou, Nikhil Ghosh, Bin Yu
2025 J jnl
Prominent Roles of Conditionally Invariant Components in Domain Adaptation: Theory and Algorithms.
J. Mach. Learn. Res.
Keru Wu, Yuansi Chen, Wooseok Ha, Bin Yu
2025 J jnl
ProxySPEX: Inference-Efficient Interpretability via Sparse Feature Interactions in LLMs.
CoRR
Landon Butler, Abhineet Agarwal, Justin Singh Kang, Yigit Efe Erginbas, Bin Yu, Kannan Ramchandran
2025 A* conf
SPEX: Scaling Feature Interaction Explanations for LLMs.
ICML
Justin Singh Kang, Landon Butler, Abhineet Agarwal, Yigit Efe Erginbas, Ramtin Pedarsani, Bin Yu, Kannan Ramchandran
2025 J jnl
SPEX: Scaling Feature Interaction Explanations for LLMs.
CoRR
Justin Singh Kang, Landon Butler, Abhineet Agarwal, Yigit Efe Erginbas, Ramtin Pedarsani, Kannan Ramchandran, Bin Yu
2025 J jnl
The Effect of SGD Batch Size on Autoencoder Learning: Sparsity, Sharpness, and Feature Learning.
J. Mach. Learn. Res.
Nikhil Ghosh, Spencer Frei, Wooseok Ha, Bin Yu
2025 J jnl
The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS).
CoRR
Andrew Ferguson, Marisa Lafleur, Lars Ruthotto, Jesse Thaler, Yuan-Sen Ting, Pratyush Tiwary, Soledad Villar, E. Paulo Alves, Jeremy Avigad, Simon Billinge, Camille L. Bilodeau, Keith Brown, Emmanuel J. Candès, Arghya Chattopadhyay, Bingqing Cheng, Jonathan Clausen, Connor W. Coley, Andrew J. Connolly, Fred Daum, Sijia S. Dong, Chrisy Xiyu Du, Cora Dvorkin, Cristiano Fanelli, Eric B. Ford, Luis Manuel Frutos, Nicolás García Trillos, Cecilia Garraffo, Robert Ghrist, Rafael Gómez-Bombarelli, Gianluca Guadagni, Sreelekha Guggilam, Sergei Gukov, Juan B. Gutierrez, Salman Habib, Johannes Hachmann, Boris Hanin, Philip C. Harris, Murray Holland, Elizabeth Holm, Hsin-Yuan Huang, Shih-Chieh Hsu, Nick Jackson, Olexandr Isayev, Heng Ji, Aggelos K. Katsaggelos, Jeremy Kepner, Yannis G. Kevrekidis, Michelle P. Kuchera, J. Nathan Kutz, Branislava Lalic, Ann Lee, Matt LeBlanc, Josiah Lim, Rebecca Lindsey, Yongmin Liu, Peter Y. Lu, Sudhir Malik, Vuk Mandic, Vidya B. Manian, Emeka P. Mazi, Pankaj Mehta, Peter Melchior, Brice Ménard, Jennifer Ngadiuba, Stella Offner, Elsa Olivetti, Shyue Ping Ong, Christopher Rackauckas, Philippe Rigollet, Chad Risko, Philip Romero, Grant M. Rotskoff, Brett Savoie, Uros Seljak, David Shih, Gary Shiu, Dima Shlyakhtenko, Eva Silverstein, Taylor Sparks, Thomas Strohmer, Christopher Stubbs, Stephen Thomas, Suriyanarayanan Vaikuntanathan, René Vidal, Francisco Villaescusa-Navarro, Gregory Voth, Benjamin Wandelt, Rachel Ward, Melanie Weber, Risa Wechsler, Stephen Whitelam, Olaf Wiest, Mike Williams, Zhuoran Yang, Yaroslava G. Yingling, Bin Yu, Shuwen Yue, Ann Zabludoff, Huimin Zhao, Tong Zhang
2025 B conf
Towards Consistent Natural-Language Explanations via Explanation-Consistency Finetuning.
COLING
Yanda Chen, Chandan Singh, Xiaodong Liu, Simiao Zuo, Bin Yu, He He, Jianfeng Gao
2024 J jnl
A generative framework to bridge data-driven models and scientific theories in language neuroscience.
CoRR
Richard J. Antonello, Chandan Singh, Shailee Jain, Aliyah R. Hsu, Jianfeng Gao, Bin Yu, Alexander Huth
2024 A* conf
Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making.
ICLR
Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Briton Park, Tristan Naumann, Anobel Y. Odisho, Bin Yu
2024 A* conf
ED-Copilot: Reduce Emergency Department Wait Time with Language Model Diagnostic Assistance.
ICML
Liwen Sun, Abhineet Agarwal, Aaron Kornblith, Bin Yu, Chenyan Xiong
2024 J jnl
ED-Copilot: Reduce Emergency Department Wait Time with Language Model Diagnostic Assistance.
CoRR
Liwen Sun, Abhineet Agarwal, Aaron Kornblith, Bin Yu, Chenyan Xiong
2024 A* conf
Improving Prototypical Visual Explanations with Reward Reweighing, Reselection, and Retraining.
ICML
Aaron Jiaxun Li, Robin Netzorg, Zhihan Cheng, Zhuoqin Zhang, Bin Yu
2024 A* conf
KnowGraph: Knowledge-Enabled Anomaly Detection via Logical Reasoning on Graph Data.
CCS
Andy Zhou, Xiaojun Xu, Ramesh Raghunathan, Alok Lal, Xinze Guan, Bin Yu, Bo Li
2024 J jnl
KnowGraph: Knowledge-Enabled Anomaly Detection via Logical Reasoning on Graph Data.
CoRR
Andy Zhou, Xiaojun Xu, Ramesh Raghunathan, Alok Lal, Xinze Guan, Bin Yu, Bo Li
2024 A* conf
LoRA+: Efficient Low Rank Adaptation of Large Models.
ICML
Soufiane Hayou, Nikhil Ghosh, Bin Yu
2024 J jnl
LoRA+: Efficient Low Rank Adaptation of Large Models.
CoRR
Soufiane Hayou, Nikhil Ghosh, Bin Yu
2024 J jnl
Mechanistic Interpretation through Contextual Decomposition in Transformers.
CoRR
Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Anobel Y. Odisho, Peter R. Carroll, Bin Yu
2024 A* conf
Minimum-Norm Interpolation Under Covariate Shift.
ICML
Neil Mallinar, Austin Zane, Spencer Frei, Bin Yu
2024 J jnl
Minimum-Norm Interpolation Under Covariate Shift.
CoRR
Neil Mallinar, Austin Zane, Spencer Frei, Bin Yu
2024 J jnl
Rate, Explain and Cite (REC): Enhanced Explanation and Attribution in Automatic Evaluation by Large Language Models.
CoRR
Aliyah R. Hsu, James Zhu, Zhichao Wang, Bin Bi, Shubham Mehrotra, Shiva K. Pentyala, Katherine Tan, Xiang-Bo Mao, Roshanak Omrani, Sougata Chaudhuri, Regunathan Radhakrishnan, Sitaram Asur, Claire Na Cheng, Bin Yu
2024 J jnl
ScaLES: Scalable Latent Exploration Score for Pre-Trained Generative Networks.
CoRR
Omer Ronen, Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk, Bin Yu
2024 A* conf
Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs.
ICLR
Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao
2024 J jnl
The Computational Curse of Big Data for Bayesian Additive Regression Trees: A Hitting Time Analysis.
CoRR
Yan Shuo Tan, Omer Ronen, Theo Saarinen, Bin Yu
2024 A* conf
The Impact of Initialization on LoRA Finetuning Dynamics.
NeurIPS
Soufiane Hayou, Nikhil Ghosh, Bin Yu
2024 J jnl
The Impact of Initialization on LoRA Finetuning Dynamics.
CoRR
Soufiane Hayou, Nikhil Ghosh, Bin Yu
2024 J jnl
Towards Consistent Natural-Language Explanations via Explanation-Consistency Finetuning.
CoRR
Yanda Chen, Chandan Singh, Xiaodong Liu, Simiao Zuo, Bin Yu, He He, Jianfeng Gao
2024 J jnl
simChef: High-quality data science simulations in R.
J. Open Source Softw.
James Duncan, Tiffany M. Tang, Corrine F. Elliott, Philippe Boileau, Bin Yu
2023 J jnl
An Investigation into the Effects of Pre-training Data Distributions for Pathology Report Classification.
CoRR
Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Briton Park, Tristan Naumann, Anobel Y. Odisho, Bin Yu
2023 A* conf
Bridging Discrete and Backpropagation: Straight-Through and Beyond.
NeurIPS
Liyuan Liu, Chengyu Dong, Xiaodong Liu, Bin Yu, Jianfeng Gao
2023 J jnl
Bridging Discrete and Backpropagation: Straight-Through and Beyond.
CoRR
Liyuan Liu, Chengyu Dong, Xiaodong Liu, Bin Yu, Jianfeng Gao
2023 J jnl
Explaining black box text modules in natural language with language models.
CoRR
Chandan Singh, Aliyah R. Hsu, Richard J. Antonello, Shailee Jain, Alexander G. Huth, Bin Yu, Jianfeng Gao
2023 J jnl
Improving Prototypical Part Networks with Reward Reweighing, Reselection, and Retraining.
CoRR
Robin Netzorg, Jiaxun Li, Bin Yu
2023 J jnl
MDI+: A Flexible Random Forest-Based Feature Importance Framework.
CoRR
Abhineet Agarwal, Ana M. Kenney, Yan Shuo Tan, Tiffany M. Tang, Bin Yu
2023 J jnl
Prominent Roles of Conditionally Invariant Components in Domain Adaptation: Theory and Algorithms.
CoRR
Keru Wu, Yuansi Chen, Wooseok Ha, Bin Yu
2023 J jnl
Revisiting minimum description length complexity in overparameterized models.
J. Mach. Learn. Res.
Raaz Dwivedi, Chandan Singh, Bin Yu, Martin J. Wainwright
2023 J jnl
Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs.
CoRR
Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao
2023 J jnl
The Effect of SGD Batch Size on Autoencoder Learning: Sparsity, Sharpness, and Feature Learning.
CoRR
Nikhil Ghosh, Spencer Frei, Wooseok Ha, Bin Yu
2022 J jnl
A Mixing Time Lower Bound for a Simplified Version of BART.
CoRR
Omer Ronen, Theo Saarinen, Yan Shuo Tan, James Duncan, Bin Yu
2022 A conf
A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds.
AISTATS
Yan Shuo Tan, Abhineet Agarwal, Bin Yu
2022 J jnl
Fast Interpretable Greedy-Tree Sums (FIGS).
CoRR
Yan Shuo Tan, Chandan Singh, Keyan Nasseri, Abhineet Agarwal, Bin Yu
2022 J jnl
Group Probability-Weighted Tree Sums for Interpretable Modeling of Heterogeneous Data.
CoRR
Keyan Nasseri, Chandan Singh, James Duncan, Aaron Kornblith, Bin Yu
2022 A* conf
Hierarchical Shrinkage: Improving the accuracy and interpretability of tree-based models.
ICML
Abhineet Agarwal, Yan Shuo Tan, Omer Ronen, Chandan Singh, Bin Yu
2022 J jnl
Hierarchical Shrinkage: improving the accuracy and interpretability of tree-based methods.
CoRR
Abhineet Agarwal, Yan Shuo Tan, Omer Ronen, Chandan Singh, Bin Yu
2022 A* conf
The Three Stages of Learning Dynamics in High-dimensional Kernel Methods.
ICLR
Nikhil Ghosh, Song Mei, Bin Yu
2022 J jnl
Towards Robust Waveform-Based Acoustic Models.
IEEE ACM Trans. Audio Speech Lang. Process.
Dino Oglic, Zoran Cvetkovic, Peter Sollich, Steve Renals, Bin Yu
2022 J jnl
VeridicalFlow: a Python package for building trustworthy data science pipelines with PCS.
J. Open Source Softw.
James Duncan, Rush Kapoor, Abhineet Agarwal, Chandan Singh, Bin Yu
2021 J jnl
A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds.
CoRR
Yan Shuo Tan, Abhineet Agarwal, Bin Yu
2021 A* conf
Adaptive wavelet distillation from neural networks through interpretations.
NeurIPS
Wooseok Ha, Chandan Singh, François Lanusse, Srigokul Upadhyayula, Bin Yu
2021 J jnl
Adaptive wavelet distillation from neural networks through interpretations.
CoRR
Wooseok Ha, Chandan Singh, François Lanusse, Eli Song, Song Dang, Kangmin He, Srigokul Upadhyayula, Bin Yu
2021 J jnl
Interpreting and improving deep-learning models with reality checks.
CoRR
Chandan Singh, Wooseok Ha, Bin Yu
2021 J jnl
Structural Compression of Convolutional Neural Networks with Applications in Interpretability.
Frontiers Big Data
Reza Abbasi-Asl, Bin Yu
2021 J jnl
Supervised line attention for tumor attribute classification from pathology reports: Higher performance with less data.
J. Biomed. Informatics
Nicholas Altieri, Briton Park, Mara Olson, John DeNero, Anobel Y. Odisho, Bin Yu
2021 J jnl
The Three Stages of Learning Dynamics in High-Dimensional Kernel Methods.
CoRR
Nikhil Ghosh, Song Mei, Bin Yu
2021 J jnl
Towards Robust Waveform-Based Acoustic Models.
CoRR
Dino Oglic, Zoran Cvetkovic, Peter Sollich, Steve Renals, Bin Yu
2021 J jnl
imodels: a python package for fitting interpretable models.
J. Open Source Softw.
Chandan Singh, Keyan Nasseri, Yan Shuo Tan, Tiffany M. Tang, Bin Yu
2020 J jnl
Curating a COVID-19 data repository and forecasting county-level death counts in the United States.
CoRR
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
2020 J jnl
Enriched Annotations for Tumor Attribute Classification from Pathology Reports with Limited Labeled Data.
CoRR
Nick Altieri, Briton Park, Mara Olson, John DeNero, Anobel Y. Odisho, Bin Yu
2020 J jnl
Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients.
J. Mach. Learn. Res.
Yuansi Chen, Raaz Dwivedi, Martin J. Wainwright, Bin Yu
2020 J jnl
Instability, Computational Efficiency and Statistical Accuracy.
CoRR
Nhat Ho, Koulik Khamaru, Raaz Dwivedi, Martin J. Wainwright, Michael I. Jordan, Bin Yu
2020 A* conf
Interpretations are Useful: Penalizing Explanations to Align Neural Networks with Prior Knowledge.
ICML
Laura Rieger, Chandan Singh, W. James Murdoch, Bin Yu
2020 — conf
Interpreting and Improving Deep-Learning Models with Reality Checks.
xxAI@ICML
Chandan Singh, Wooseok Ha, Bin Yu
2020 J jnl
Revisiting complexity and the bias-variance tradeoff.
CoRR
Raaz Dwivedi, Chandan Singh, Bin Yu, Martin J. Wainwright
2020 A conf
Sharp Analysis of Expectation-Maximization for Weakly Identifiable Models.
AISTATS
Raaz Dwivedi, Nhat Ho, Koulik Khamaru, Martin J. Wainwright, Michael I. Jordan, Bin Yu
2020 J jnl
Stable discovery of interpretable subgroups via calibration in causal studies.
CoRR
Raaz Dwivedi, Yan Shuo Tan, Briton Park, Mian Wei, Kevin Horgan, David Madigan, Bin Yu
2020 J jnl
Transformation Importance with Applications to Cosmology.
CoRR
Chandan Singh, Wooseok Ha, François Lanusse, Vanessa Böhm, Jia Liu, Bin Yu
2020 J jnl
Unique Sharp Local Minimum in L1-minimization Complete Dictionary Learning.
J. Mach. Learn. Res.
Yu Wang, Siqi Wu, Bin Yu
2020 A conf
Veridical Data Science.
WSDM
Bin Yu
2019 A* conf
A Debiased MDI Feature Importance Measure for Random Forests.
NeurIPS
Xiao Li, Yu Wang, Sumanta Basu, Karl Kumbier, Bin Yu
2019 J jnl
A Debiased MDI Feature Importance Measure for Random Forests.
CoRR
Xiao Li, Yu Wang, Sumanta Basu, Karl Kumbier, Bin Yu
2019 J jnl
Challenges with EM in application to weakly identifiable mixture models.
CoRR
Raaz Dwivedi, Nhat Ho, Koulik Khamaru, Martin J. Wainwright, Michael I. Jordan, Bin Yu
2019 J jnl
Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees.
CoRR
Summer Devlin, Chandan Singh, W. James Murdoch, Bin Yu
2019 J jnl
Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients.
CoRR
Yuansi Chen, Raaz Dwivedi, Martin J. Wainwright, Bin Yu
2019 — conf
Hierarchical interpretations for neural network predictions.
ICLR (Poster)
Chandan Singh, W. James Murdoch, Bin Yu
2019 J jnl
Interpretable machine learning: definitions, methods, and applications.
CoRR
W. James Murdoch, Chandan Singh, Karl Kumbier, Reza Abbasi-Asl, Bin Yu
2019 J jnl
Interpretations are useful: penalizing explanations to align neural networks with prior knowledge.
CoRR
Laura Rieger, Chandan Singh, W. James Murdoch, Bin Yu
2019 J jnl
Log-concave sampling: Metropolis-Hastings algorithms are fast.
J. Mach. Learn. Res.
Raaz Dwivedi, Yuansi Chen, Martin J. Wainwright, Bin Yu
2019 J jnl
Three principles of data science: predictability, computability, and stability (PCS).
CoRR
Bin Yu, Karl Kumbier
2019 J jnl
Unique Sharp Local Minimum in $\ell_1$-minimization Complete Dictionary Learning.
CoRR
Yu Wang, Siqi Wu, Bin Yu
2018 J jnl
Artificial intelligence and statistics.
Frontiers Inf. Technol. Electron. Eng.
Bin Yu, Karl Kumbier
2018 — conf
Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs.
ICLR
W. James Murdoch, Peter J. Liu, Bin Yu
2018 J jnl
Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs.
CoRR
W. James Murdoch, Peter J. Liu, Bin Yu
2018 J jnl
Fast MCMC Sampling Algorithms on Polytopes.
J. Mach. Learn. Res.
Yuansi Chen, Raaz Dwivedi, Martin J. Wainwright, Bin Yu
2018 J jnl
Hierarchical interpretations for neural network predictions.
CoRR
Chandan Singh, W. James Murdoch, Bin Yu
2018 A* conf
Log-concave sampling: Metropolis-Hastings algorithms are fast!
COLT
Raaz Dwivedi, Yuansi Chen, Martin J. Wainwright, Bin Yu
2018 J jnl
Refining interaction search through signed iterative Random Forests.
CoRR
Karl Kumbier, Sumanta Basu, James B. Brown, Susan Celniker, Bin Yu
2018 J jnl
Stability and Convergence Trade-off of Iterative Optimization Algorithms.
CoRR
Yuansi Chen, Chi Jin, Bin Yu
2018 — conf
Three principles of data science: predictability, computability, and stability (PCS).
IEEE BigData
Bin Yu
2018 J jnl
iRF: extracting interactions from random forests.
J. Open Source Softw.
Sumanta Basu, Karl Kumbier, James B. Brown, Bin Yu
2017 J jnl
Artificial Intelligence and Statistics.
CoRR
Bin Yu, Karl Kumbier
2017 J jnl
Interpreting Convolutional Neural Networks Through Compression.
CoRR
Reza Abbasi-Asl, Bin Yu
2017 J jnl
Structural Compression of Convolutional Neural Networks Based on Greedy Filter Pruning.
CoRR
Reza Abbasi-Asl, Bin Yu
2017 A* conf
Three Principles of Data Science: Predictability, Stability and Computability.
KDD
Bin Yu
2017 — conf
Vaidya walk: A sampling algorithm based on the volumetric barrier.
Allerton
Yuansi Chen, Raaz Dwivedi, Martin J. Wainwright, Bin Yu
2016 — conf
DataLab: a version data management and analytics system.
BIGDSE@ICSE
Yang Zhang, Fangzhou Xu, Erwin Frise, Siqi Wu, Bin Yu, Wei Xu
2016 Misc conf
Do retinal ganglion cells project natural scenes to their principal subspace and whiten them?
ACSSC
Reza Abbasi-Asl, Cengiz Pehlevan, Bin Yu, Dmitri B. Chklovskii
2016 J jnl
Formulas for Counting the Sizes of Markov Equivalence Classes of Directed Acyclic Graphs.
CoRR
Yangbo He, Bin Yu
2016 A conf
Supervised Neighborhoods for Distributed Nonparametric Regression.
AISTATS
Adam E. Bloniarz, Ameet Talwalkar, Bin Yu, Christopher Wu
2016 J jnl
Ten Simple Rules for Effective Statistical Practice.
PLoS Comput. Biol.
Robert E. Kass, Brian S. Caffo, Marie Davidian, Xiao-Li Meng, Bin Yu, Nancy Reid
2015 J jnl
A statistical perspective on algorithmic leveraging.
J. Mach. Learn. Res.
Ping Ma, Michael W. Mahoney, Bin Yu
2015 J jnl
Counting and exploring sizes of Markov equivalence classes of directed acyclic graphs.
J. Mach. Learn. Res.
Yangbo He, Jinzhu Jia, Bin Yu
2014 A* conf
A Statistical Perspective on Algorithmic Leveraging.
ICML
Ping Ma, Michael W. Mahoney, Bin Yu
2014 B conf
Changepoint Analysis for Efficient Variant Calling.
RECOMB
Adam E. Bloniarz, Ameet Talwalkar, Jonathan Terhorst, Michael I. Jordan, David A. Patterson, Bin Yu, Yun S. Song
2014 J jnl
Concise comparative summaries (CCS) of large text corpora with a human experiment.
CoRR
Jinzhu Jia, Luke Miratrix, Bin Yu, Brian Gawalt, Laurent El Ghaoui, Luke Barnesmoore, Sophie Clavier
2014 J jnl
Early stopping and non-parametric regression: an optimal data-dependent stopping rule.
J. Mach. Learn. Res.
Garvesh Raskutti, Martin J. Wainwright, Bin Yu
2014 J jnl
Error Rate Bounds and Iterative Weighted Majority Voting for Crowdsourcing.
CoRR
Hongwei Li, Bin Yu
2014 Misc conf
Impact of regularization on spectral clustering.
ITA
Antony Joseph, Bin Yu
2014 J jnl
Statistical guarantees for the EM algorithm: From population to sample-based analysis.
CoRR
Sivaraman Balakrishnan, Martin J. Wainwright, Bin Yu
2013 J jnl
A Statistical Perspective on Algorithmic Leveraging.
CoRR
Ping Ma, Michael W. Mahoney, Bin Yu
2013 J jnl
Error Rate Bounds in Crowdsourcing Models.
CoRR
Hongwei Li, Bin Yu, Dengyong Zhou
2013 J jnl
Supervised feature selection in graphs with path coding penalties and network flows.
J. Mach. Learn. Res.
Julien Mairal, Bin Yu
2012 J jnl
Complexity Analysis of the Lasso Regularization Path
CoRR
Julien Mairal, Bin Yu
2012 A* conf
Complexity Analysis of the Lasso Regularization Path.
ICML
Julien Mairal, Bin Yu
2012 J jnl
Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming.
J. Mach. Learn. Res.
Garvesh Raskutti, Martin J. Wainwright, Bin Yu
2012 C conf
Multiple-kernel learning-based unmixing algorithm for estimation of cloud fractions with MODIS and CloudSat data.
IGARSS
Yanfeng Gu, Shizhe Wang, Tao Shi, Yinghui Lu, Eugene E. Clothiaux, Bin Yu
2012 J jnl
Reversible MCMC on Markov equivalence classes of sparse directed acyclic graphs
CoRR
Yangbo He, Jinzhu Jia, Bin Yu
2012 J jnl
Supervised Feature Selection in Graphs with Path Coding Penalties and Network Flows
CoRR
Julien Mairal, Bin Yu
2011 J jnl
Combined Features and Kernel Design for Noise Robust Phoneme Classification Using Support Vector Machines.
IEEE Trans. Speech Audio Process.
Jibran Yousafzai, Peter Sollich, Zoran Cvetkovic, Bin Yu
2011 J jnl
Distributed modal identification using restricted auto regressive models.
Int. J. Syst. Sci.
Shamim N. Pakzad, Guilherme V. Rocha, Bin Yu
2011 — conf
Early stopping for non-parametric regression: An optimal data-dependent stopping rule.
Allerton
Garvesh Raskutti, Martin J. Wainwright, Bin Yu
2011 J jnl
Minimax Rates of Estimation for High-Dimensional Linear Regression Over
IEEE Trans. Inf. Theory
Garvesh Raskutti, Martin J. Wainwright, Bin Yu
2011 J jnl
Preface.
Math. Program.
Alexandre d'Aspremont, Francis R. Bach, Inderjit S. Dhillon, Bin Yu
2011 — conf
SBA-term: Sparse Bilingual Association for Terms.
ICSC
Xinyu Dai, Jinzhu Jia, Laurent El Ghaoui, Bin Yu
2010 J jnl
A unified framework for high-dimensional analysis of $M$-estimators with decomposable regularizers
CoRR
Sahand N. Negahban, Pradeep Ravikumar, Martin J. Wainwright, Bin Yu
2010 — conf
Discovering word associations in news media via feature selection and sparse classification.
Multimedia Information Retrieval
Brian Gawalt, Jinzhu Jia, Luke Miratrix, Laurent El Ghaoui, Bin Yu, Sophie Clavier
2010 J jnl
Minimax-optimal rates for sparse additive models over kernel classes via convex programming.
CoRR
Garvesh Raskutti, Martin J. Wainwright, Bin Yu
2010 A* conf
Multi-Task Sparse Discriminant Analysis (MtSDA) with Overlapping Categories.
AAAI
Yahong Han, Fei Wu, Jinzhu Jia, Yueting Zhuang, Bin Yu
2010 — conf
Predicting Execution Time of Computer Programs Using Sparse Polynomial Regression.
NIPS
Ling Huang, Jinzhu Jia, Bin Yu, Byung-Gon Chun, Petros Maniatis, Mayur Naik
2010 J jnl
Restricted Eigenvalue Properties for Correlated Gaussian Designs.
J. Mach. Learn. Res.
Garvesh Raskutti, Martin J. Wainwright, Bin Yu
2009 — conf
A unified framework for high-dimensional analysis of $M$-estimators with decomposable regularizers.
NIPS
Sahand N. Negahban, Pradeep Ravikumar, Martin J. Wainwright, Bin Yu
2009 J jnl
Information in the Nonstationary Case.
Neural Comput.
Vincent Q. Vu, Bin Yu, Robert E. Kass
2009 — conf
Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothness.
NIPS
Garvesh Raskutti, Martin J. Wainwright, Bin Yu
2009 — conf
Minimax rates of convergence for high-dimensional regression under ℓq-ball sparsity.
Allerton
Garvesh Raskutti, Martin J. Wainwright, Bin Yu
2009 J jnl
Minimax rates of estimation for high-dimensional linear regression over $\ell_q$-balls.
CoRR
Garvesh Raskutti, Martin J. Wainwright, Bin Yu
2009 Misc conf
Some statistical issues in estimating information in neural spike trains.
ICASSP
Vincent Q. Vu, Bin Yu, Robert E. Kass
2008 — conf
Combined PLP - Acoustic waveform classification for robust phoneme recognition using support vector machines.
EUSIPCO
Jibran Yousafzai, Zoran Cvetkovic, Peter Sollich, Bin Yu
2008 A* conf
Data spectroscopy: learning mixture models using eigenspaces of convolution operators.
ICML
Tao Shi, Mikhail Belkin, Bin Yu
2008 J jnl
Information In The Non-Stationary Case
CoRR
Vincent Q. Vu, Bin Yu, Robert E. Kass
2008 — conf
Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of l
NIPS
Pradeep Ravikumar, Garvesh Raskutti, Martin J. Wainwright, Bin Yu
2008 — conf
Nonparametric sparse hierarchical models describe V1 fMRI responses to natural images.
NIPS
Pradeep Ravikumar, Vincent Q. Vu, Bin Yu, Thomas Naselaris, Kendrick N. Kay, Jack L. Gallant
2008 — conf
Towards robust phoneme classification: Augmentation of PLP models with acoustic waveforms.
EUSIPCO
Matthew Ager, Zoran Cvetkovic, Peter Sollich, Bin Yu
2007 J jnl
Embracing Statistical Challenges in the Information Technology Age.
Technometrics
Bin Yu
2007 J jnl
Stagewise Lasso.
J. Mach. Learn. Res.
Peng Zhao, Bin Yu
2006 J jnl
A fast lightweight approach to origin-destination IP traffic estimation using partial measurements.
IEEE Trans. Inf. Theory
Gang Liang, Nina Taft, Bin Yu
2006 A* conf
Approximation Lasso Methods for Language Modeling.
ACL
Jianfeng Gao, Hisami Suzuki, Bin Yu
2006 J jnl
On Model Selection Consistency of Lasso.
J. Mach. Learn. Res.
Peng Zhao, Bin Yu
2006 J jnl
Sparse Boosting.
J. Mach. Learn. Res.
Peter Bühlmann, Bin Yu
2004 J jnl
Guest Editorial: Special Issue on Machine Learning Methods in Signal Processing.
IEEE Trans. Signal Process.
Meir Feder, Mário A. T. Figueiredo, Alfred O. Hero III, Chin-Hui Lee, Hans-Andrea Loeliger, Robert D. Nowak, Andrew C. Singer, Bin Yu
2004 B conf
Maximum entropy models: convergence rates and applications in dynamic system monitoring.
ISIT
Gang Liang, Bin Yu, Nina Taft
2003 J jnl
Maximum pseudo likelihood estimation in network tomography.
IEEE Trans. Signal Process.
Gang Liang, Bin Yu
2003 J jnl
Microarray image compression: SLOCO and the effect of information loss.
Signal Process.
Rebecka Jörnsten, Wei Wang, Bin Yu, Kannan Ramchandran
2003 A* conf
On the Convergence of Boosting Procedures.
ICML
Tong Zhang, Bin Yu
2003 A* conf
Pseudo Likelihood Estimation in Network Tomography.
INFOCOM
Gang Liang, Bin Yu
2003 J jnl
Simultaneous Gene Clustering and Subset Selection for Sample Classification Via MDL.
Bioinform.
Rebecka Jörnsten, Bin Yu
2002 — conf
Compression of cDNA and inkjet microarray images.
ICIP (3)
Rebecka Jörnsten, Bin Yu, Wei Wang, Kannan Ramchandran
2002 — conf
Compression of cDNA microarray images.
ISBI
Rebecka Jörnsten, Bin Yu
2002 J jnl
Internet tomography.
IEEE Signal Process. Mag.
Mark Coates, Alfred O. Hero III, Robert D. Nowak, Bin Yu
2002 J jnl
Perceptual audio coding using adaptive pre- and post-filters and lossless compression.
IEEE Trans. Speech Audio Process.
Gerald Schuller, Bin Yu, Dawei Huang, Bernd Edler
2001 Misc conf
Lossless coding of audio signals using cascaded prediction.
ICASSP
Gerald Schuller, Bin Yu, Dawei Huang
2001 B conf
Low Delay Perpetually Lossless Coding of Audio Signals.
Data Compression Conference
Sean Dorward, Dawei Huang, Serap A. Savari, Gerald Schuller, Bin Yu
2000 J jnl
Adaptive wavelet thresholding for image denoising and compression.
IEEE Trans. Image Process.
S. Grace Chang, Bin Yu, Martin Vetterli
2000 J jnl
Iterated logarithmic expansions of the pathwise code lengths for exponential families.
IEEE Trans. Inf. Theory
Lei Li, Bin Yu
2000 J jnl
Spatially adaptive wavelet thresholding with context modeling for image denoising.
IEEE Trans. Image Process.
S. Grace Chang, Bin Yu, Martin Vetterli
2000 J jnl
Wavelet thresholding for multiple noisy image copies.
IEEE Trans. Image Process.
S. Grace Chang, Bin Yu, Martin Vetterli
2000 J jnl
Wavelet thresholding via MDL for natural images.
IEEE Trans. Inf. Theory
Mark Hansen, Bin Yu
1999 J jnl
Image subband coding using context-based classification and adaptive quantization.
IEEE Trans. Image Process.
Youngjun Yoo, Antonio Ortega, Bin Yu
1999 J jnl
Penalized discriminant analysis of in situ hyperspectral data for conifer species recognition.
IEEE Trans. Geosci. Remote. Sens.
Bin Yu, Michael Ostland, Peng Gong, Ruiliang Pu
1998 — conf
Multiple Copy Image Denoising via Wavelet Thresholding.
ICIP (1)
S. Grace Chang, Bin Yu, Martin Vetterli
1998 — conf
Spatially Adaptive Wavelet Thresholding with Context Modeling for Image Denoising.
ICIP (1)
S. Grace Chang, Bin Yu, Martin Vetterli
1998 J jnl
The Minimum Description Length Principle in Coding and Modeling.
IEEE Trans. Inf. Theory
Andrew R. Barron, Jorma Rissanen, Bin Yu
1997 — conf
Image Denoising via Lossy Compression and Wavelet Thresholding.
ICIP (1)
S. Grace Chang, Bin Yu, Martin Vetterli
1996 — conf
Adaptive quantization of image subbands with efficient overhead rate selection.
ICIP (2)
Youngjun Yoo, Antonio Ortega, Bin Yu
1996 J jnl
Lower Bounds on Expected Redundancy for Nonparametric Classes.
IEEE Trans. Inf. Theory
Bin Yu
1993 J jnl
A rate of convergence result for a universal D-semifaithful code.
IEEE Trans. Inf. Theory
Bin Yu, Terry P. Speed
1992 J jnl
Density estimation by stochastic complexity.
IEEE Trans. Inf. Theory
Jorma Rissanen, Terry P. Speed, Bin Yu