Yu, Bin

63 publications

ICLRW 2025 Adaptive Test-Time Intervention for Concept Bottleneck Models Matthew Shen, Aliyah R. Hsu, Abhineet Agarwal, Bin Yu

ICML 2025 Benefits of Early Stopping in Gradient Descent for Overparameterized Logistic Regression Jingfeng Wu, Peter Bartlett, Matus Telgarsky, Bin Yu

ICLR 2025 Efficient Automated Circuit Discovery in Transformers Using Contextual Decomposition Aliyah R. Hsu, Georgia Zhou, Yeshwanth Cherapanamjeri, Yaxuan Huang, Anobel Odisho, Peter R. Carroll, Bin Yu

JMLR 2025 Instability, Computational Efficiency and Statistical Accuracy Nhat Ho, Koulik Khamaru, Raaz Dwivedi, Martin J. Wainwright, Michael I. Jordan, Bin Yu

ICML 2025 Mitigating Over-Exploration in Latent Space Optimization Using Les Omer Ronen, Ahmed Imtiaz Humayun, Richard Baraniuk, Randall Balestriero, Bin Yu

JMLR 2025 Prominent Roles of Conditionally Invariant Components in Domain Adaptation: Theory and Algorithms Keru Wu, Yuansi Chen, Wooseok Ha, Bin Yu

NeurIPS 2025 ProxySPEX: Inference-Efficient Interpretability via Sparse Feature Interactions in LLMs Landon Butler, Abhineet Agarwal, Justin Singh Kang, Yigit Efe Erginbas, Bin Yu, Kannan Ramchandran

ICML 2025 SPEX: Scaling Feature Interaction Explanations for LLMs Justin Singh Kang, Landon Butler, Abhineet Agarwal, Yigit Efe Erginbas, Ramtin Pedarsani, Bin Yu, Kannan Ramchandran

ICLRW 2025 SPEX: Scaling Feature Interaction Explanations for LLMs Justin Singh Kang, Landon Butler, Abhineet Agarwal, Yigit Efe Erginbas, Ramtin Pedarsani, Bin Yu, Kannan Ramchandran

JMLR 2025 The Effect of SGD Batch Size on Autoencoder Learning: Sparsity, Sharpness, and Feature Learning Nikhil Ghosh, Spencer Frei, Wooseok Ha, Bin Yu

ICLR 2024 Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Briton Park, Tristan Naumann, Anobel Odisho, Bin Yu

ICML 2024 ED-Copilot: Reduce Emergency Department Wait Time with Language Model Diagnostic Assistance Liwen Sun, Abhineet Agarwal, Aaron Kornblith, Bin Yu, Chenyan Xiong

ICML 2024 Improving Prototypical Visual Explanations with Reward Reweighing, Reselection, and Retraining Aaron Jiaxun Li, Robin Netzorg, Zhihan Cheng, Zhuoqin Zhang, Bin Yu

COLT 2024 Large Stepsize Gradient Descent for Logistic Loss: Non-Monotonicity of the Loss Improves Optimization Efficiency Jingfeng Wu, Peter L. Bartlett, Matus Telgarsky, Bin Yu

ICML 2024 LoRA+: Efficient Low Rank Adaptation of Large Models Soufiane Hayou, Nikhil Ghosh, Bin Yu

ICML 2024 Minimum-Norm Interpolation Under Covariate Shift Neil Rohit Mallinar, Austin Zane, Spencer Frei, Bin Yu

ICMLW 2024 ScaLES: Scalable Latent Exploration Score for Pre-Trained Generative Networks Omer Ronen, Ahmed Imtiaz Humayun, Randall Balestriero, Richard Baraniuk, Bin Yu

ICLR 2024 Tell Your Model Where to Attend: Post-Hoc Attention Steering for LLMs Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao

NeurIPS 2024 The Impact of Initialization on LoRA Finetuning Dynamics Soufiane Hayou, Nikhil Ghosh, Bin Yu

NeurIPS 2023 Bridging Discrete and Backpropagation: Straight-Through and Beyond Liyuan Liu, Chengyu Dong, Xiaodong Liu, Bin Yu, Jianfeng Gao

NeurIPSW 2023 Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making Aliyah Hsu, Yeshwanth Cherapanamjeri, Briton Park, Tristan Naumann, Anobel Odisho, Bin Yu

NeurIPSW 2023 Explaining Black Box Text Modules in Natural Language with Language Models Chandan Singh, Aliyah Hsu, Richard Antonello, Shailee Jain, Alexander Huth, Bin Yu, Jianfeng Gao

JMLR 2023 Revisiting Minimum Description Length Complexity in Overparameterized Models Raaz Dwivedi, Chandan Singh, Bin Yu, Martin Wainwright

NeurIPSW 2023 Tell Your Model Where to Attend: Post-Hoc Attention Steering for LLMs Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao

AISTATS 2022 A Cautionary Tale on Fitting Decision Trees to Data from Additive Models: Generalization Lower Bounds Yan Shuo Tan, Abhineet Agarwal, Bin Yu

CVPR 2022 C2AM Loss: Chasing a Better Decision Boundary for Long-Tail Object Detection Tong Wang, Yousong Zhu, Yingying Chen, Chaoyang Zhao, Bin Yu, Jinqiao Wang, Ming Tang

NeurIPSW 2022 Gradient Dynamics of Single-Neuron Autoencoders on Orthogonal Data Nikhil Ghosh, Spencer Frei, Wooseok Ha, Bin Yu

ICML 2022 Hierarchical Shrinkage: Improving the Accuracy and Interpretability of Tree-Based Models. Abhineet Agarwal, Yan Shuo Tan, Omer Ronen, Chandan Singh, Bin Yu

NeurIPSW 2022 Offline Evaluation in RL: Soft Stability Weighting to Combine Fitted Q-Learning and Model-Based Methods Briton Park, Carrie Wu, Bin Yu, Angela Zhou

ICLR 2022 The Three Stages of Learning Dynamics in High-Dimensional Kernel Methods Nikhil Ghosh, Song Mei, Bin Yu

NeurIPS 2021 Adaptive Wavelet Distillation from Neural Networks Through Interpretations Wooseok Ha, Chandan Singh, Francois Lanusse, Srigokul Upadhyayula, Bin Yu

WACV 2021 Fast Kernelized Correlation Filter Without Boundary Effect Ming Tang, Linyu Zheng, Bin Yu, Jinqiao Wang

ICCV 2021 High-Performance Discriminative Tracking with Transformers Bin Yu, Ming Tang, Linyu Zheng, Guibo Zhu, Jinqiao Wang, Hao Feng, Xuetao Feng, Hanqing Lu

JMLR 2020 Fast Mixing of Metropolized Hamiltonian Monte Carlo: Benefits of Multi-Step Gradients Yuansi Chen, Raaz Dwivedi, Martin J. Wainwright, Bin Yu

ICML 2020 Interpretations Are Useful: Penalizing Explanations to Align Neural Networks with Prior Knowledge Laura Rieger, Chandan Singh, William Murdoch, Bin Yu

AISTATS 2020 Sharp Analysis of Expectation-Maximization for Weakly Identifiable Models Raaz Dwivedi, Nhat Ho, Koulik Khamaru, Martin Wainwright, Michael Jordan, Bin Yu

JMLR 2020 Unique Sharp Local Minimum in L1-Minimization Complete Dictionary Learning Yu Wang, Siqi Wu, Bin Yu

NeurIPS 2019 A Debiased MDI Feature Importance Measure for Random Forests Xiao Li, Yu Wang, Sumanta Basu, Karl Kumbier, Bin Yu

ICLR 2019 Hierarchical Interpretations for Neural Network Predictions Chandan Singh, W. James Murdoch, Bin Yu

JMLR 2019 Log-Concave Sampling: Metropolis-Hastings Algorithms Are Fast Raaz Dwivedi, Yuansi Chen, Martin J. Wainwright, Bin Yu

ICLR 2018 Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs W. James Murdoch, Peter J. Liu, Bin Yu

JMLR 2018 Fast MCMC Sampling Algorithms on Polytopes Yuansi Chen, Raaz Dwivedi, Martin J. Wainwright, Bin Yu

COLT 2018 Log-Concave Sampling: Metropolis-Hastings Algorithms Are Fast! Raaz Dwivedi, Yuansi Chen, Martin J. Wainwright, Bin Yu

AISTATS 2016 Supervised Neighborhoods for Distributed Nonparametric Regression Adam E. Bloniarz, Ameet Talwalkar, Bin Yu, Christopher Wu

JMLR 2015 A Statistical Perspective on Algorithmic Leveraging Ping Ma, Michael W. Mahoney, Bin Yu

JMLR 2015 Counting and Exploring Sizes of Markov Equivalence Classes of Directed Acyclic Graphs Yangbo He, Jinzhu Jia, Bin Yu

ICML 2014 A Statistical Perspective on Algorithmic Leveraging Ping Ma, Michael Mahoney, Bin Yu

JMLR 2014 Early Stopping and Non-Parametric Regression: An Optimal Data-Dependent Stopping Rule Garvesh Raskutti, Martin J. Wainwright, Bin Yu

JMLR 2013 Supervised Feature Selection in Graphs with Path Coding Penalties and Network Flows Julien Mairal, Bin Yu

ICML 2012 Complexity Analysis of the Lasso Regularization Path Julien Mairal, Bin Yu

JMLR 2012 Minimax-Optimal Rates for Sparse Additive Models over Kernel Classes via Convex Programming Garvesh Raskutti, Martin J. Wainwright, Bin Yu

AAAI 2010 Multi-Task Sparse Discriminant Analysis (MtSDA) with Overlapping Categories Yahong Han, Fei Wu, Jinzhu Jia, Yueting Zhuang, Bin Yu

NeurIPS 2010 Predicting Execution Time of Computer Programs Using Sparse Polynomial Regression Ling Huang, Jinzhu Jia, Bin Yu, Byung-gon Chun, Petros Maniatis, Mayur Naik

JMLR 2010 Restricted Eigenvalue Properties for Correlated Gaussian Designs Garvesh Raskutti, Martin J. Wainwright, Bin Yu

NeurIPS 2009 A Unified Framework for High-Dimensional Analysis of $m$-Estimators with Decomposable Regularizers Sahand Negahban, Bin Yu, Martin J. Wainwright, Pradeep K. Ravikumar

NeurIPS 2009 Lower Bounds on Minimax Rates for Nonparametric Regression with Additive Sparsity and Smoothness Garvesh Raskutti, Bin Yu, Martin J. Wainwright

ICML 2008 Data Spectroscopy: Learning Mixture Models Using Eigenspaces of Convolution Operators Tao Shi, Mikhail Belkin, Bin Yu

NeurIPS 2008 Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of \boldmath$\ell_1$-Regularized MLE Garvesh Raskutti, Bin Yu, Martin J. Wainwright, Pradeep K. Ravikumar

NeurIPS 2008 Nonparametric Sparse Hierarchical Models Describe V1 fMRI Responses to Natural Images Vincent Q. Vu, Bin Yu, Thomas Naselaris, Kendrick Kay, Jack Gallant, Pradeep K. Ravikumar

JMLR 2007 Stagewise Lasso Peng Zhao, Bin Yu

JMLR 2006 On Model Selection Consistency of Lasso Peng Zhao, Bin Yu

JMLR 2006 Sparse Boosting Peter Bühlmann, Bin Yu

ICML 2003 On the Convergence of Boosting Procedures Tong Zhang, Bin Yu