Density estimation by stochastic complexity. - Jorma Rissanen; Terry P. Speed; Bin Yu 001 (IEEE Trans. Inf. Theory, 1992)

A rate of convergence result for a universal D-semifaithful code. - Bin Yu 001; Terry P. Speed (IEEE Trans. Inf. Theory, 1993)

Adaptive quantization of image subbands with efficient overhead rate selection. - Youngjun Yoo; Antonio Ortega; Bin Yu 001 (ICIP (2), 1996)

Lower Bounds on Expected Redundancy for Nonparametric Classes. - Bin Yu 001 (IEEE Trans. Inf. Theory, 1996)

Image Denoising via Lossy Compression and Wavelet Thresholding. - S. Grace Chang; Bin Yu 001; Martin Vetterli (ICIP (1), 1997)

Multiple Copy Image Denoising via Wavelet Thresholding. - S. Grace Chang; Bin Yu 001; Martin Vetterli (ICIP (1), 1998)

The Minimum Description Length Principle in Coding and Modeling. - Andrew R. Barron; Jorma Rissanen; Bin Yu 001 (IEEE Trans. Inf. Theory, 1998)

Penalized discriminant analysis of in situ hyperspectral data for conifer species recognition. - Bin Yu 001; Michael Ostland; Peng Gong; Ruiliang Pu (IEEE Trans. Geosci. Remote. Sens., 1999)

Image subband coding using context-based classification and adaptive quantization. - Youngjun Yoo; Antonio Ortega; Bin Yu 001 (IEEE Trans. Image Process., 1999)

Spatially adaptive wavelet thresholding with context modeling for image denoising. - S. Grace Chang; Bin Yu 001; Martin Vetterli (IEEE Trans. Image Process., 2000)

Adaptive wavelet thresholding for image denoising and compression. - S. Grace Chang; Bin Yu 001; Martin Vetterli (IEEE Trans. Image Process., 2000)

Wavelet thresholding for multiple noisy image copies. - S. Grace Chang; Bin Yu 001; Martin Vetterli (IEEE Trans. Image Process., 2000)

Wavelet thresholding via MDL for natural images. - Mark Hansen; Bin Yu 001 (IEEE Trans. Inf. Theory, 2000)

Iterated logarithmic expansions of the pathwise code lengths for exponential families. - Lei Li; Bin Yu 001 (IEEE Trans. Inf. Theory, 2000)

Low Delay Perpetually Lossless Coding of Audio Signals. - Sean Dorward; Dawei Huang; Serap A. Savari; Gerald Schuller; Bin Yu 001 (Data Compression Conference, 2001)

Lossless coding of audio signals using cascaded prediction. - Gerald Schuller; Bin Yu 001; Dawei Huang (ICASSP, 2001)

Compression of cDNA and inkjet microarray images. - Rebecka Jörnsten; Bin Yu 001; Wei Wang 039; Kannan Ramchandran (ICIP (3), 2002)

Compression of cDNA microarray images. - Rebecka Jörnsten; Bin Yu 001 (ISBI, 2002)

Internet tomography. - Mark Coates; Alfred O. Hero III; Robert D. Nowak; Bin Yu 001 (IEEE Signal Process. Mag., 2002)

Perceptual audio coding using adaptive pre- and post-filters and lossless compression. - Gerald Schuller; Bin Yu 001; Dawei Huang; Bernd Edler (IEEE Trans. Speech Audio Process., 2002)

On the Convergence of Boosting Procedures. - Tong Zhang 001; Bin Yu 001 (ICML, 2003)

Pseudo Likelihood Estimation in Network Tomography. - Gang Liang; Bin Yu 001 (INFOCOM, 2003)

Simultaneous Gene Clustering and Subset Selection for Sample Classification Via MDL. - Rebecka Jörnsten; Bin Yu 001 (Bioinform., 2003)

Microarray image compression: SLOCO and the effect of information loss. - Rebecka Jörnsten; Wei Wang 039; Bin Yu 001; Kannan Ramchandran (Signal Process., 2003)

Maximum pseudo likelihood estimation in network tomography. - Gang Liang; Bin Yu 001 (IEEE Trans. Signal Process., 2003)

Maximum entropy models: convergence rates and applications in dynamic system monitoring. - Gang Liang; Bin Yu 001; Nina Taft (ISIT, 2004)

Guest Editorial: Special Issue on Machine Learning Methods in Signal Processing. - Meir Feder; Mário A. T. Figueiredo; Alfred O. Hero III; Chin-Hui Lee; Hans-Andrea Loeliger; Robert D. Nowak; Andrew C. Singer; Bin Yu 001 (IEEE Trans. Signal Process., 2004)

Approximation Lasso Methods for Language Modeling. - Jianfeng Gao 001; Hisami Suzuki; Bin Yu 001 (ACL, 2006)

Sparse Boosting. - Peter Bühlmann; Bin Yu 001 (J. Mach. Learn. Res., 2006)

On Model Selection Consistency of Lasso. - Peng Zhao; Bin Yu 001 (J. Mach. Learn. Res., 2006)

A fast lightweight approach to origin-destination IP traffic estimation using partial measurements. - Gang Liang; Nina Taft; Bin Yu 001 (IEEE Trans. Inf. Theory, 2006)

Stagewise Lasso. - Peng Zhao; Bin Yu 001 (J. Mach. Learn. Res., 2007)

Embracing Statistical Challenges in the Information Technology Age. - Bin Yu 001 (Technometrics, 2007)

Towards robust phoneme classification: Augmentation of PLP models with acoustic waveforms. - Matthew Ager; Zoran Cvetkovic; Peter Sollich; Bin Yu 001 (EUSIPCO, 2008)

Combined PLP - Acoustic waveform classification for robust phoneme recognition using support vector machines. - Jibran Yousafzai; Zoran Cvetkovic; Peter Sollich; Bin Yu 001 (EUSIPCO, 2008)

Data spectroscopy: learning mixture models using eigenspaces of convolution operators. - Tao Shi; Mikhail Belkin; Bin Yu 001 (ICML, 2008)

Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of l1-regularized MLE. - Pradeep Ravikumar; Garvesh Raskutti; Martin J. Wainwright; Bin Yu 001 (NIPS, 2008)

Nonparametric sparse hierarchical models describe V1 fMRI responses to natural images. - Pradeep Ravikumar; Vincent Q. Vu; Bin Yu 001; Thomas Naselaris; Kendrick N. Kay; Jack L. Gallant (NIPS, 2008)

Information In The Non-Stationary Case - Vincent Q. Vu; Bin Yu 001; Robert E. Kass (CoRR, 2008)

Minimax rates of convergence for high-dimensional regression under ℓq-ball sparsity. - Garvesh Raskutti; Martin J. Wainwright; Bin Yu 001 (Allerton, 2009)

Some statistical issues in estimating information in neural spike trains. - Vincent Q. Vu; Bin Yu 001; Robert E. Kass (ICASSP, 2009)

A unified framework for high-dimensional analysis of $M$-estimators with decomposable regularizers. - Sahand N. Negahban; Pradeep Ravikumar; Martin J. Wainwright; Bin Yu 001 (NIPS, 2009)

Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothness. - Garvesh Raskutti; Martin J. Wainwright; Bin Yu 001 (NIPS, 2009)

Minimax rates of estimation for high-dimensional linear regression over $ ell_q$-balls. - Garvesh Raskutti; Martin J. Wainwright; Bin Yu 001 (CoRR, 2009)

Information in the Nonstationary Case. - Vincent Q. Vu; Bin Yu 001; Robert E. Kass (Neural Comput., 2009)

Multi-Task Sparse Discriminant Analysis (MtSDA) with Overlapping Categories. - Yahong Han; Fei Wu 001; Jinzhu Jia; Yueting Zhuang; Bin Yu 001 (AAAI, 2010)

Discovering word associations in news media via feature selection and sparse classification. - Brian Gawalt; Jinzhu Jia; Luke Miratrix; Laurent El Ghaoui; Bin Yu 001; Sophie Clavier (Multimedia Information Retrieval, 2010)

Predicting Execution Time of Computer Programs Using Sparse Polynomial Regression. - Ling Huang 001; Jinzhu Jia; Bin Yu 001; Byung-Gon Chun; Petros Maniatis; Mayur Naik (NIPS, 2010)

Restricted Eigenvalue Properties for Correlated Gaussian Designs. - Garvesh Raskutti; Martin J. Wainwright; Bin Yu 001 (J. Mach. Learn. Res., 2010)

Early stopping for non-parametric regression: An optimal data-dependent stopping rule. - Garvesh Raskutti; Martin J. Wainwright; Bin Yu 001 (Allerton, 2011)

SBA-term: Sparse Bilingual Association for Terms. - Xinyu Dai; Jinzhu Jia; Laurent El Ghaoui; Bin Yu 001 (ICSC, 2011)

Distributed modal identification using restricted auto regressive models. - Shamim N. Pakzad; Guilherme V. Rocha; Bin Yu 001 (Int. J. Syst. Sci., 2011)

Preface. - Alexandre d'Aspremont; Francis R. Bach; Inderjit S. Dhillon; Bin Yu 001 (Math. Program., 2011)

Combined Features and Kernel Design for Noise Robust Phoneme Classification Using Support Vector Machines. - Jibran Yousafzai; Peter Sollich; Zoran Cvetkovic; Bin Yu 001 (IEEE Trans. Speech Audio Process., 2011)

Minimax Rates of Estimation for High-Dimensional Linear Regression Over q -Balls. - Garvesh Raskutti; Martin J. Wainwright; Bin Yu 001 (IEEE Trans. Inf. Theory, 2011)

Complexity Analysis of the Lasso Regularization Path. - Julien Mairal; Bin Yu 001 (ICML, 2012)

Multiple-kernel learning-based unmixing algorithm for estimation of cloud fractions with MODIS and CloudSat data. - Yanfeng Gu; Shizhe Wang; Tao Shi; Yinghui Lu; Eugene E. Clothiaux; Bin Yu 001 (IGARSS, 2012)

Reversible MCMC on Markov equivalence classes of sparse directed acyclic graphs - Yangbo He; Jinzhu Jia; Bin Yu 001 (CoRR, 2012)

Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming. - Garvesh Raskutti; Martin J. Wainwright; Bin Yu 001 (J. Mach. Learn. Res., 2012)

Error Rate Bounds in Crowdsourcing Models. - Hongwei Li; Bin Yu 001; Dengyong Zhou (CoRR, 2013)

Supervised feature selection in graphs with path coding penalties and network flows. - Julien Mairal; Bin Yu 001 (J. Mach. Learn. Res., 2013)

Impact of regularization on spectral clustering. - Antony Joseph; Bin Yu 001 (ITA, 2014)

Changepoint Analysis for Efficient Variant Calling. - Adam E. Bloniarz; Ameet Talwalkar; Jonathan Terhorst; Michael I. Jordan; David A. Patterson 001; Bin Yu 001; Yun S. Song (RECOMB, 2014)

Statistical guarantees for the EM algorithm: From population to sample-based analysis. - Sivaraman Balakrishnan; Martin J. Wainwright; Bin Yu 001 (CoRR, 2014)

Concise comparative summaries (CCS) of large text corpora with a human experiment. - Jinzhu Jia; Luke Miratrix; Bin Yu 001; Brian Gawalt; Laurent El Ghaoui; Luke Barnesmoore; Sophie Clavier (CoRR, 2014)

Error Rate Bounds and Iterative Weighted Majority Voting for Crowdsourcing. - Hongwei Li; Bin Yu 001 (CoRR, 2014)

Early stopping and non-parametric regression: an optimal data-dependent stopping rule. - Garvesh Raskutti; Martin J. Wainwright; Bin Yu 001 (J. Mach. Learn. Res., 2014)

Counting and exploring sizes of Markov equivalence classes of directed acyclic graphs. - Yangbo He; Jinzhu Jia; Bin Yu 001 (J. Mach. Learn. Res., 2015)

A statistical perspective on algorithmic leveraging. - Ping Ma 001; Michael W. Mahoney; Bin Yu 001 (J. Mach. Learn. Res., 2015)

Do retinal ganglion cells project natural scenes to their principal subspace and whiten them? - Reza Abbasi-Asl; Cengiz Pehlevan; Bin Yu 001; Dmitri B. Chklovskii (ACSSC, 2016)

Supervised Neighborhoods for Distributed Nonparametric Regression. - Adam E. Bloniarz; Ameet Talwalkar; Bin Yu 001; Christopher Wu (AISTATS, 2016)

DataLab: a version data management and analytics system. - Yang Zhang; Fangzhou Xu; Erwin Frise; Siqi Wu; Bin Yu 001; Wei Xu 005 (BIGDSE@ICSE, 2016)

Formulas for Counting the Sizes of Markov Equivalence Classes of Directed Acyclic Graphs. - Yangbo He; Bin Yu 001 (CoRR, 2016)

Ten Simple Rules for Effective Statistical Practice. - Robert E. Kass; Brian S. Caffo; Marie Davidian; Xiao-Li Meng; Bin Yu 001; Nancy Reid (PLoS Comput. Biol., 2016)

Vaidya walk: A sampling algorithm based on the volumetric barrier. - Yuansi Chen; Raaz Dwivedi; Martin J. Wainwright; Bin Yu 001 (Allerton, 2017)

Three Principles of Data Science: Predictability, Stability and Computability. - Bin Yu 001 (KDD, 2017)

Structural Compression of Convolutional Neural Networks Based on Greedy Filter Pruning. - Reza Abbasi-Asl; Bin Yu 001 (CoRR, 2017)

Interpreting Convolutional Neural Networks Through Compression. - Reza Abbasi-Asl; Bin Yu 001 (CoRR, 2017)

Three principles of data science: predictability, computability, and stability (PCS). - Bin Yu 001 (IEEE BigData, 2018)

Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs. - W. James Murdoch; Peter J. Liu; Bin Yu 001 (ICLR, 2018)

Stability and Convergence Trade-off of Iterative Optimization Algorithms. - Yuansi Chen; Chi Jin 001; Bin Yu 001 (CoRR, 2018)

Refining interaction search through signed iterative Random Forests. - Karl Kumbier; Sumanta Basu; James B. Brown; Susan Celniker; Bin Yu 001 (CoRR, 2018)

Fast MCMC Sampling Algorithms on Polytopes. - Yuansi Chen; Raaz Dwivedi; Martin J. Wainwright; Bin Yu 001 (J. Mach. Learn. Res., 2018)

iRF: extracting interactions from random forests. - Sumanta Basu; Karl Kumbier; James B. Brown; Bin Yu 001 (J. Open Source Softw., 2018)

Artificial intelligence and statistics. - Bin Yu 001; Karl Kumbier (Frontiers Inf. Technol. Electron. Eng., 2018)

Hierarchical interpretations for neural network predictions. - Chandan Singh; W. James Murdoch; Bin Yu 001 (ICLR (Poster), 2019)

A Debiased MDI Feature Importance Measure for Random Forests. - Xiao Li; Yu Wang 075; Sumanta Basu; Karl Kumbier; Bin Yu 001 (NeurIPS, 2019)

Interpretable machine learning: definitions, methods, and applications. - W. James Murdoch; Chandan Singh; Karl Kumbier; Reza Abbasi-Asl; Bin Yu 001 (CoRR, 2019)

Three principles of data science: predictability, computability, and stability (PCS). - Bin Yu 001; Karl Kumbier (CoRR, 2019)

Challenges with EM in application to weakly identifiable mixture models. - Raaz Dwivedi; Nhat Ho; Koulik Khamaru; Martin J. Wainwright; Michael I. Jordan; Bin Yu 001 (CoRR, 2019)

Unique Sharp Local Minimum in $ ell_1$-minimization Complete Dictionary Learning. - Yu Wang 075; Siqi Wu; Bin Yu 001 (CoRR, 2019)

Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees. - Summer Devlin; Chandan Singh; W. James Murdoch; Bin Yu 001 (CoRR, 2019)

Log-concave sampling: Metropolis-Hastings algorithms are fast. - Raaz Dwivedi; Yuansi Chen; Martin J. Wainwright; Bin Yu 001 (J. Mach. Learn. Res., 2019)

Sharp Analysis of Expectation-Maximization for Weakly Identifiable Models. - Raaz Dwivedi; Nhat Ho; Koulik Khamaru; Martin J. Wainwright; Michael I. Jordan; Bin Yu 001 (AISTATS, 2020)

Interpretations are Useful: Penalizing Explanations to Align Neural Networks with Prior Knowledge. - Laura Rieger; Chandan Singh; W. James Murdoch; Bin Yu 001 (ICML, 2020)

Interpreting and Improving Deep-Learning Models with Reality Checks. - Chandan Singh; Wooseok Ha; Bin Yu 001 (xxAI@ICML, 2020)

Veridical Data Science. - Bin Yu 001 (WSDM, 2020)

Transformation Importance with Applications to Cosmology. - Chandan Singh; Wooseok Ha; François Lanusse; Vanessa Böhm; Jia Liu; Bin Yu 001 (CoRR, 2020)

Curating a COVID-19 data repository and forecasting county-level death counts in the United States. - Nick Altieri 001; Rebecca L. Barter; James Duncan 002; Raaz Dwivedi; Karl Kumbier; Xiao Li; Robert Netzorg; Briton Park; Chandan Singh; Yan Shuo Tan; Tiffany M. Tang; Yu Wang 075; et al. (CoRR, 2020)

Instability, Computational Efficiency and Statistical Accuracy. - Nhat Ho; Koulik Khamaru; Raaz Dwivedi; Martin J. Wainwright; Michael I. Jordan; Bin Yu 001 (CoRR, 2020)

Revisiting complexity and the bias-variance tradeoff. - Raaz Dwivedi; Chandan Singh; Bin Yu 001; Martin J. Wainwright (CoRR, 2020)

Stable discovery of interpretable subgroups via calibration in causal studies. - Raaz Dwivedi; Yan Shuo Tan; Briton Park; Mian Wei; Kevin Horgan; David Madigan; Bin Yu 001 (CoRR, 2020)

Enriched Annotations for Tumor Attribute Classification from Pathology Reports with Limited Labeled Data. - Nick Altieri 001; Briton Park; Mara Olson; John DeNero; Anobel Y. Odisho; Bin Yu 001 (CoRR, 2020)

Unique Sharp Local Minimum in L1-minimization Complete Dictionary Learning. - Yu Wang 075; Siqi Wu; Bin Yu 001 (J. Mach. Learn. Res., 2020)

Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients. - Yuansi Chen; Raaz Dwivedi; Martin J. Wainwright; Bin Yu 001 (J. Mach. Learn. Res., 2020)

Adaptive wavelet distillation from neural networks through interpretations. - Wooseok Ha; Chandan Singh; François Lanusse; Srigokul Upadhyayula; Bin Yu 001 (NeurIPS, 2021)

Adaptive wavelet distillation from neural networks through interpretations. - Wooseok Ha; Chandan Singh; François Lanusse; Eli Song; Song Dang; Kangmin He; Srigokul Upadhyayula; Bin Yu 001 (CoRR, 2021)

Structural Compression of Convolutional Neural Networks with Applications in Interpretability. - Reza Abbasi-Asl; Bin Yu 001 (Frontiers Big Data, 2021)

Supervised line attention for tumor attribute classification from pathology reports: Higher performance with less data. - Nicholas Altieri 001; Briton Park; Mara Olson; John DeNero; Anobel Y. Odisho; Bin Yu 001 (J. Biomed. Informatics, 2021)

imodels: a python package for fitting interpretable models. - Chandan Singh; Keyan Nasseri; Yan Shuo Tan; Tiffany M. Tang; Bin Yu 001 (J. Open Source Softw., 2021)

A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds. - Yan Shuo Tan; Abhineet Agarwal; Bin Yu 001 (AISTATS, 2022)

The Three Stages of Learning Dynamics in High-dimensional Kernel Methods. - Nikhil Ghosh; Song Mei; Bin Yu 001 (ICLR, 2022)

Hierarchical Shrinkage: Improving the accuracy and interpretability of tree-based models. - Abhineet Agarwal; Yan Shuo Tan; Omer Ronen; Chandan Singh; Bin Yu 001 (ICML, 2022)

Fast Interpretable Greedy-Tree Sums (FIGS). - Yan Shuo Tan; Chandan Singh; Keyan Nasseri; Abhineet Agarwal; Bin Yu 001 (CoRR, 2022)

Hierarchical Shrinkage: improving the accuracy and interpretability of tree-based methods. - Abhineet Agarwal; Yan Shuo Tan; Omer Ronen; Chandan Singh; Bin Yu 001 (CoRR, 2022)

Group Probability-Weighted Tree Sums for Interpretable Modeling of Heterogeneous Data. - Keyan Nasseri; Chandan Singh; James Duncan 002; Aaron Kornblith; Bin Yu 001 (CoRR, 2022)

A Mixing Time Lower Bound for a Simplified Version of BART. - Omer Ronen; Theo Saarinen; Yan Shuo Tan; James Duncan 002; Bin Yu 001 (CoRR, 2022)

VeridicalFlow: a Python package for building trustworthy data science pipelines with PCS. - James Duncan 002; Rush Kapoor; Abhineet Agarwal; Chandan Singh; Bin Yu 001 (J. Open Source Softw., 2022)

Towards Robust Waveform-Based Acoustic Models. - Dino Oglic; Zoran Cvetkovic; Peter Sollich; Steve Renals; Bin Yu 001 (IEEE ACM Trans. Audio Speech Lang. Process., 2022)

Bridging Discrete and Backpropagation: Straight-Through and Beyond. - Liyuan Liu; Chengyu Dong; Xiaodong Liu 003; Bin Yu 001; Jianfeng Gao 001 (NeurIPS, 2023)

Explaining black box text modules in natural language with language models. - Chandan Singh; Aliyah R. Hsu; Richard J. Antonello; Shailee Jain; Alexander G. Huth; Bin Yu 001; Jianfeng Gao 001 (CoRR, 2023)

An Investigation into the Effects of Pre-training Data Distributions for Pathology Report Classification. - Aliyah R. Hsu; Yeshwanth Cherapanamjeri; Briton Park; Tristan Naumann; Anobel Y. Odisho; Bin Yu 001 (CoRR, 2023)

MDI+: A Flexible Random Forest-Based Feature Importance Framework. - Abhineet Agarwal; Ana M. Kenney; Yan Shuo Tan; Tiffany M. Tang; Bin Yu 001 (CoRR, 2023)

Improving Prototypical Part Networks with Reward Reweighing, Reselection, and Retraining. - Robin Netzorg; Jiaxun Li 002; Bin Yu 001 (CoRR, 2023)

The Effect of SGD Batch Size on Autoencoder Learning: Sparsity, Sharpness, and Feature Learning. - Nikhil Ghosh; Spencer Frei; Wooseok Ha; Bin Yu 001 (CoRR, 2023)

Prominent Roles of Conditionally Invariant Components in Domain Adaptation: Theory and Algorithms. - Keru Wu; Yuansi Chen; Wooseok Ha; Bin Yu 001 (CoRR, 2023)

Revisiting minimum description length complexity in overparameterized models. - Raaz Dwivedi; Chandan Singh; Bin Yu 001; Martin J. Wainwright (J. Mach. Learn. Res., 2023)

KnowGraph: Knowledge-Enabled Anomaly Detection via Logical Reasoning on Graph Data. - Andy Zhou; Xiaojun Xu; Ramesh Raghunathan; Alok Lal; Xinze Guan; Bin Yu 001; Bo Li 026 (CCS, 2024)

Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making. - Aliyah R. Hsu; Yeshwanth Cherapanamjeri; Briton Park; Tristan Naumann; Anobel Y. Odisho; Bin Yu 001 (ICLR, 2024)

Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs. - Qingru Zhang; Chandan Singh; Liyuan Liu; Xiaodong Liu 003; Bin Yu 001; Jianfeng Gao 001; Tuo Zhao (ICLR, 2024)

LoRA+: Efficient Low Rank Adaptation of Large Models. - Soufiane Hayou; Nikhil Ghosh; Bin Yu 001 (ICML, 2024)

Improving Prototypical Visual Explanations with Reward Reweighing, Reselection, and Retraining. - Aaron Jiaxun Li; Robin Netzorg; Zhihan Cheng; Zhuoqin Zhang; Bin Yu 001 (ICML, 2024)

Minimum-Norm Interpolation Under Covariate Shift. - Neil Mallinar; Austin Zane; Spencer Frei; Bin Yu 001 (ICML, 2024)

ED-Copilot: Reduce Emergency Department Wait Time with Language Model Diagnostic Assistance. - Liwen Sun; Abhineet Agarwal; Aaron Kornblith; Bin Yu 001; Chenyan Xiong (ICML, 2024)

The Impact of Initialization on LoRA Finetuning Dynamics. - Soufiane Hayou; Nikhil Ghosh; Bin Yu 001 (NeurIPS, 2024)

ScaLES: Scalable Latent Exploration Score for Pre-Trained Generative Networks. - Omer Ronen; Ahmed Imtiaz Humayun; Randall Balestriero; Richard G. Baraniuk; Bin Yu 001 (CoRR, 2024)

The Computational Curse of Big Data for Bayesian Additive Regression Trees: A Hitting Time Analysis. - Yan Shuo Tan; Omer Ronen; Theo Saarinen; Bin Yu 001 (CoRR, 2024)

Mechanistic Interpretation through Contextual Decomposition in Transformers. - Aliyah R. Hsu; Yeshwanth Cherapanamjeri; Anobel Y. Odisho; Peter R. Carroll; Bin Yu 001 (CoRR, 2024)

A generative framework to bridge data-driven models and scientific theories in language neuroscience. - Richard J. Antonello; Chandan Singh; Shailee Jain; Aliyah R. Hsu; Jianfeng Gao 001; Bin Yu 001; Alexander Huth (CoRR, 2024)

Rate, Explain and Cite (REC): Enhanced Explanation and Attribution in Automatic Evaluation by Large Language Models. - 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; et al. (CoRR, 2024)

simChef: High-quality data science simulations in R. - James Duncan 002; Tiffany M. Tang; Corrine F. Elliott; Philippe Boileau; Bin Yu 001 (J. Open Source Softw., 2024)

Towards Consistent Natural-Language Explanations via Explanation-Consistency Finetuning. - Yanda Chen; Chandan Singh; Xiaodong Liu 003; Simiao Zuo; Bin Yu 001; He He 001; Jianfeng Gao 001 (COLING, 2025)

Efficient Automated Circuit Discovery in Transformers using Contextual Decomposition. - Aliyah R. Hsu; Georgia Zhou; Yeshwanth Cherapanamjeri; Yaxuan Huang; Anobel Y. Odisho; Peter R. Carroll; Bin Yu 001 (ICLR, 2025)

SPEX: Scaling Feature Interaction Explanations for LLMs. - Justin Singh Kang; Landon Butler; Abhineet Agarwal; Yigit Efe Erginbas; Ramtin Pedarsani; Kannan Ramchandran; Bin Yu 001 (CoRR, 2025)

Enhancing CBMs Through Binary Distillation with Applications to Test-Time Intervention. - Matthew Shen; Aliyah R. Hsu; Abhineet Agarwal; Bin Yu 001 (CoRR, 2025)

PCS-UQ: Uncertainty Quantification via the Predictability-Computability-Stability Framework. - Abhineet Agarwal; Michael Xiao; Rebecca L. Barter; Omer Ronen; Boyu Fan; Bin Yu 001 (CoRR, 2025)

ProxySPEX: Inference-Efficient Interpretability via Sparse Feature Interactions in LLMs. - Landon Butler; Abhineet Agarwal; Justin Singh Kang; Yigit Efe Erginbas; Bin Yu 001; Kannan Ramchandran (CoRR, 2025)

Local MDI+: Local Feature Importances for Tree-Based Models. - Zhongyuan Liang; Zachary T. Rewolinski; Abhineet Agarwal; Tiffany M. Tang; Bin Yu 001 (CoRR, 2025)

PLoP: Precise LoRA Placement for Efficient Finetuning of Large Models. - Soufiane Hayou; Nikhil Ghosh; Bin Yu 001 (CoRR, 2025)