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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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Journal Articles
- 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)- 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 2010
- [j24]Garvesh Raskutti, Martin J. Wainwright, Bin Yu:
Restricted Eigenvalue Properties for Correlated Gaussian Designs. J. Mach. Learn. Res. 11: 2241-2259 (2010) - 2009
- [j23]Vincent Q. Vu, Bin Yu, Robert E. Kass:
Information in the Nonstationary Case. Neural Comput. 21(3): 688-703 (2009) - 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) - 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) - 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) - 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) - 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) - 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) - 1996
- [j3]Bin Yu:
Lower Bounds on Expected Redundancy for Nonparametric Classes. IEEE Trans. Inf. Theory 42(1): 272-275 (1996) - 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)
Conference and Workshop Papers
- 2025
- [c60]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 - [c59]Aliyah R. Hsu, Georgia Zhou, Yeshwanth Cherapanamjeri, Yaxuan Huang, Anobel Y. Odisho, Peter R. Carroll, Bin Yu:
Efficient Automated Circuit Discovery in Transformers using Contextual Decomposition. ICLR 2025 - 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 - 2023
- [c50]Liyuan Liu, Chengyu Dong, Xiaodong Liu, Bin Yu, Jianfeng Gao:
Bridging Discrete and Backpropagation: Straight-Through and Beyond. NeurIPS 2023 - 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 - 2021
- [c46]Wooseok Ha, Chandan Singh, François Lanusse, Srigokul Upadhyayula, Bin Yu:
Adaptive wavelet distillation from neural networks through interpretations. NeurIPS 2021: 20669-20682 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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
- [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 - 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 - 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 - 2006
- [c12]Jianfeng Gao, Hisami Suzuki, Bin Yu:
Approximation Lasso Methods for Language Modeling. ACL 2006 - 2004
- [c11]Gang Liang, Bin Yu, Nina Taft:
Maximum entropy models: convergence rates and applications in dynamic system monitoring. ISIT 2004: 168 - 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
- [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 - 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
- [c1]Youngjun Yoo, Antonio Ortega, Bin Yu:
Adaptive quantization of image subbands with efficient overhead rate selection. ICIP (2) 1996: 361-364
Informal and Other Publications
- 2025
- [i68]Justin Singh Kang, Landon Butler, Abhineet Agarwal, Yigit Efe Erginbas, Ramtin Pedarsani, Kannan Ramchandran, Bin Yu:
SPEX: Scaling Feature Interaction Explanations for LLMs. CoRR abs/2502.13870 (2025) - [i67]Matthew Shen, Aliyah R. Hsu, Abhineet Agarwal, Bin Yu:
Enhancing CBMs Through Binary Distillation with Applications to Test-Time Intervention. CoRR abs/2503.06730 (2025) - [i66]Abhineet Agarwal, Michael Xiao, Rebecca L. Barter, Omer Ronen, Boyu Fan, Bin Yu:
PCS-UQ: Uncertainty Quantification via the Predictability-Computability-Stability Framework. CoRR abs/2505.08784 (2025) - [i65]Landon Butler, Abhineet Agarwal, Justin Singh Kang, Yigit Efe Erginbas, Bin Yu, Kannan Ramchandran:
ProxySPEX: Inference-Efficient Interpretability via Sparse Feature Interactions in LLMs. CoRR abs/2505.17495 (2025) - [i64]Zhongyuan Liang, Zachary T. Rewolinski, Abhineet Agarwal, Tiffany M. Tang, Bin Yu:
Local MDI+: Local Feature Importances for Tree-Based Models. CoRR abs/2506.08928 (2025) - [i63]Soufiane Hayou, Nikhil Ghosh, Bin Yu:
PLoP: Precise LoRA Placement for Efficient Finetuning of Large Models. CoRR abs/2506.20629 (2025) - [i62]Andrew Ferguson, Marisa Lafleur, Lars Ruthotto, Jesse Thaler, Yuan-Sen Ting, Pratyush Tiwary, Soledad Villar, E. Paulo Alves, Jeremy Avigad, Simon Billinge, Camille Bilodeau, Keith Brown, Emmanuel J. Candès, Arghya Chattopadhyay, Bingqing Cheng, Jonathan Clausen, Connor W. Coley, Andrew J. Connolly, Fred Daum, Sijia 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. Gutiérrez, 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:
The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS). CoRR abs/2509.02661 (2025) - 2024
- [i61]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) - [i60]Soufiane Hayou, Nikhil Ghosh, Bin Yu:
LoRA+: Efficient Low Rank Adaptation of Large Models. CoRR abs/2402.12354 (2024) - [i59]Neil Mallinar, Austin Zane, Spencer Frei, Bin Yu:
Minimum-Norm Interpolation Under Covariate Shift. CoRR abs/2404.00522 (2024) - [i58]Soufiane Hayou, Nikhil Ghosh, Bin Yu:
The Impact of Initialization on LoRA Finetuning Dynamics. CoRR abs/2406.08447 (2024) - [i57]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) - [i56]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) - [i55]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) - [i54]Richard J. 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) - [i53]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) - [i52]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:
Rate, Explain and Cite (REC): Enhanced Explanation and Attribution in Automatic Evaluation by Large Language Models. CoRR abs/2411.02448 (2024) - 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 J. 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
- [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
- [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
- [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) - 2019
- [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
- [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
- [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
- [i13]Yangbo He, Bin Yu:
Formulas for Counting the Sizes of Markov Equivalence Classes of Directed Acyclic Graphs. CoRR abs/1610.07921 (2016) - 2014
- [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
- [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
- [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) - 2010
- [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) - 2009
- [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
- [i1]Vincent Q. Vu, Bin Yu, Robert E. Kass:
Information In The Non-Stationary Case. CoRR abs/0806.3978 (2008)
Coauthor Index
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