Yuheng Bu

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 60

Top Topics

Generalization Error

Dirichlet Distribution

Information Bottleneck

Top Venues

Publications

Haobo Chen, Gregory W. Wornell, Yuheng Bu
Gibbs-Based Information Criteria and the Over-Parameterized Regime. AISTATS (2024)
Jongha Jon Ryu, Maohao Shen, Soumya Ghosh, Yuheng Bu, Prasanna Sattigeri, Subhro Das, Gregory W. Wornell
Improved Evidential Deep Learning via a Mixture of Dirichlet Distributions. CoRR (2024)
Chongyang Shi, Yuheng Bu, Jie Fu
Information-Theoretic Opacity-Enforcement in Markov Decision Processes. CoRR (2024)
Jongha Jon Ryu, Xiangxiang Xu, H. S. Melihcan Erol, Yuheng Bu, Lizhong Zheng, Gregory W. Wornell
Operator SVD with Neural Networks via Nested Low-Rank Approximation. CoRR (2024)
Yepeng Liu, Yuheng Bu
Adaptive Text Watermark for Large Language Models. CoRR (2024)
Firas Laakom, Yuheng Bu, Moncef Gabbouj
Class-wise Generalization Error: an Information-Theoretic Analysis. CoRR (2024)
Haobo Chen, Gholamali Aminian, Yuheng Bu
An Algorithm for Computing the Capacity of Symmetrized KL Information for Discrete Channels. CoRR (2024)
Gholamali Aminian, Yuheng Bu, Laura Toni, Miguel R. D. Rodrigues, Gregory W. Wornell
Information-Theoretic Characterizations of Generalization Error for the Gibbs Algorithm. IEEE Trans. Inf. Theory 70 (1) (2024)
Maohao Shen, Yuheng Bu, Gregory W. Wornell
On Balancing Bias and Variance in Unsupervised Multi-Source-Free Domain Adaptation. ICML (2023)
Yuheng Bu, Harsha Vardhan Tetali, Gholamali Aminian, Miguel R. D. Rodrigues, Gregory W. Wornell
On the Generalization Error of Meta Learning for the Gibbs Algorithm. CoRR (2023)
Abhin Shah, Maohao Shen, Jongha Jon Ryu, Subhro Das, Prasanna Sattigeri, Yuheng Bu, Gregory W. Wornell
Group Fairness with Uncertainty in Sensitive Attributes. CoRR (2023)
Haiyun He, Gholamali Aminian, Yuheng Bu, Miguel R. D. Rodrigues, Vincent Y. F. Tan
How Does Pseudo-Labeling Affect the Generalization Error of the Semi-Supervised Gibbs Algorithm? AISTATS (2023)
Maohao Shen, Soumya Ghosh, Prasanna Sattigeri, Subhro Das, Yuheng Bu, Gregory W. Wornell
Reliable Gradient-free and Likelihood-free Prompt Tuning. CoRR (2023)
Haobo Chen, Yuheng Bu, Gregory W. Wornell
SGLD-Based Information Criteria and the Over-Parameterized Regime. CoRR (2023)
Amir Weiss, Alejandro Lancho, Yuheng Bu, Gregory W. Wornell
A Bilateral Bound on the Mean-Square Error for Estimation in Model Mismatch. ISIT (2023)
Bo Hu, Yuheng Bu, José C. Príncipe
Feature Learning in Image Hierarchies using Functional Maximal Correlation. CoRR (2023)
Maohao Shen, Yuheng Bu, Prasanna Sattigeri, Soumya Ghosh, Subhro Das, Gregory W. Wornell
Post-hoc Uncertainty Learning Using a Dirichlet Meta-Model. AAAI (2023)
Yuheng Bu, Harsha Vardhan Tetali, Gholamali Aminian, Miguel R. D. Rodrigues, Gregory W. Wornell
On the Generalization Error of Meta Learning for the Gibbs Algorithm. ISIT (2023)
Maohao Shen, Soumya Ghosh, Prasanna Sattigeri, Subhro Das, Yuheng Bu, Gregory W. Wornell
Reliable Gradient-free and Likelihood-free Prompt Tuning. EACL (Findings) (2023)
Amir Weiss, Alejandro Lancho, Yuheng Bu, Gregory W. Wornell
A Bilateral Bound on the Mean-Square Error for Estimation in Model Mismatch. CoRR (2023)
Maohao Shen, Yuheng Bu, Gregory W. Wornell
On the Benefits of Selectivity in Pseudo-Labeling for Unsupervised Multi-Source-Free Domain Adaptation. CoRR (2022)
Gary C. F. Lee, Amir Weiss, Alejandro Lancho, Jennifer Tang, Yuheng Bu, Yury Polyanskiy, Gregory W. Wornell
Exploiting Temporal Structures of Cyclostationary Signals for Data-Driven Single-Channel Source Separation. CoRR (2022)
Yuheng Bu, Gholamali Aminian, Laura Toni, Gregory W. Wornell, Miguel R. D. Rodrigues
Characterizing and Understanding the Generalization Error of Transfer Learning with Gibbs Algorithm. AISTATS (2022)
Abhin Shah, Yuheng Bu, Joshua K. Lee, Subhro Das, Rameswar Panda, Prasanna Sattigeri, Gregory W. Wornell
Selective Regression under Fairness Criteria. ICML (2022)
Gholamali Aminian, Yuheng Bu, Laura Toni, Miguel R. D. Rodrigues, Gregory W. Wornell
Information-theoretic Characterizations of Generalization Error for the Gibbs Algorithm. CoRR (2022)
Alejandro Lancho, Amir Weiss, Gary C. F. Lee, Jennifer Tang, Yuheng Bu, Yury Polyanskiy, Gregory W. Wornell
Data-Driven Blind Synchronization and Interference Rejection for Digital Communication Signals. GLOBECOM (2022)
Joshua K. Lee, Yuheng Bu, Prasanna Sattigeri, Rameswar Panda, Gregory W. Wornell, Leonid Karlinsky, Rogério Feris
A Maximal Correlation Approach to Imposing Fairness in Machine Learning. ICASSP (2022)
Gholamali Aminian, Yuheng Bu, Gregory W. Wornell, Miguel R. D. Rodrigues
Tighter Expected Generalization Error Bounds via Convexity of Information Measures. ISIT (2022)
Gary C. F. Lee, Amir Weiss, Alejandro Lancho, Jennifer Tang, Yuheng Bu, Yury Polyanskiy, Gregory W. Wornell
Exploiting Temporal Structures of Cyclostationary Signals for Data-Driven Single-Channel Source Separation. MLSP (2022)
Joshua K. Lee, Yuheng Bu, Prasanna Sattigeri, Rameswar Panda, Gregory W. Wornell, Leonid Karlinsky, Rogério Schmidt Feris
A Maximal Correlation Framework for Fair Machine Learning. Entropy 24 (4) (2022)
Alejandro Lancho, Amir Weiss, Gary C. F. Lee, Jennifer Tang, Yuheng Bu, Yury Polyanskiy, Gregory W. Wornell
Data-Driven Blind Synchronization and Interference Rejection for Digital Communication Signals. CoRR (2022)
Maohao Shen, Yuheng Bu, Prasanna Sattigeri, Soumya Ghosh, Subhro Das, Gregory W. Wornell
Post-hoc Uncertainty Learning using a Dirichlet Meta-Model. CoRR (2022)
Gholamali Aminian, Yuheng Bu, Gregory W. Wornell, Miguel R. D. Rodrigues
Tighter Expected Generalization Error Bounds via Convexity of Information Measures. CoRR (2022)
Haiyun He, Gholamali Aminian, Yuheng Bu, Miguel R. D. Rodrigues, Vincent Y. F. Tan
How Does Pseudo-Labeling Affect the Generalization Error of the Semi-Supervised Gibbs Algorithm? CoRR (2022)
Abhin Shah, Yuheng Bu, Joshua Ka-Wing Lee, Subhro Das, Rameswar Panda, Prasanna Sattigeri, Gregory W. Wornell
Selective Regression Under Fairness Criteria. CoRR (2021)
Yuheng Bu, Gholamali Aminian, Laura Toni, Miguel R. D. Rodrigues, Gregory W. Wornell
Characterizing and Understanding the Generalization Error of Transfer Learning with Gibbs Algorithm. CoRR (2021)
Gholamali Aminian, Yuheng Bu, Laura Toni, Miguel R. D. Rodrigues, Gregory W. Wornell
An Exact Characterization of the Generalization Error for the Gibbs Algorithm. NeurIPS (2021)
Gholamali Aminian, Yuheng Bu, Laura Toni, Miguel R. D. Rodrigues, Gregory W. Wornell
Characterizing the Generalization Error of Gibbs Algorithm with Symmetrized KL information. CoRR (2021)
Yuheng Bu, Weihao Gao, Shaofeng Zou, Venugopal V. Veeravalli
Population Risk Improvement with Model Compression: An Information-Theoretic Approach. Entropy 23 (10) (2021)
Joshua K. Lee, Yuheng Bu, Deepta Rajan, Prasanna Sattigeri, Rameswar Panda, Subhro Das, Gregory W. Wornell
Fair Selective Classification Via Sufficiency. ICML (2021)
Yuheng Bu, Tony Wang, Gregory W. Wornell
SDP Methods for Sensitivity-Constrained Privacy Funnel and Information Bottleneck Problems. ISIT (2021)
Yuheng Bu, Weihao Gao, Shaofeng Zou, Venugopal V. Veeravalli
Information-Theoretic Understanding of Population Risk Improvement with Model Compression. AAAI (2020)
Yuheng Bu, Shaofeng Zou, Venugopal V. Veeravalli
Tightening Mutual Information-Based Bounds on Generalization Error. IEEE J. Sel. Areas Inf. Theory 1 (1) (2020)
Joshua K. Lee, Yuheng Bu, Prasanna Sattigeri, Rameswar Panda, Gregory W. Wornell, Leonid Karlinsky, Rogério Feris
A Maximal Correlation Approach to Imposing Fairness in Machine Learning. CoRR (2020)
Yuheng Bu, Shaofeng Zou, Venugopal V. Veeravalli
Linear-Complexity Exponentially-Consistent Tests for Universal Outlying Sequence Detection. IEEE Trans. Signal Process. 67 (8) (2019)
Yuheng Bu, Shaofeng Zou, Venugopal V. Veeravalli
Tightening Mutual Information Based Bounds on Generalization Error. CoRR (2019)
Yuheng Bu, Jiaxun Lu, Venugopal V. Veeravalli
Active and Adaptive Sequential Learning with Per Time-step Excess Risk Guarantees. ACSSC (2019)
Yuheng Bu, Jiaxun Lu, Venugopal V. Veeravalli
Model Change Detection with Application to Machine Learning. ICASSP (2019)
Yuheng Bu, Shaofeng Zou, Venugopal V. Veeravalli
Tightening Mutual Information Based Bounds on Generalization Error. ISIT (2019)
Yuheng Bu, Weihao Gao, Shaofeng Zou, Venugopal V. Veeravalli
Information-Theoretic Understanding of Population Risk Improvement with Model Compression. CoRR (2019)
Craig Wilson, Yuheng Bu, Venugopal V. Veeravalli
Adaptive Sequential Machine Learning. CoRR (2019)
Yuheng Bu, Jiaxun Lu, Venugopal V. Veeravalli
Active and Adaptive Sequential learning. CoRR (2018)
Yuheng Bu, Kevin Small
Active Learning in Recommendation Systems with Multi-level User Preferences. CoRR (2018)
Yuheng Bu, Jiaxun Lu, Venugopal V. Veeravalli
Model change detection with application to machine learning. CoRR (2018)
Yuheng Bu, Shaofeng Zou, Yingbin Liang, Venugopal V. Veeravalli
Estimation of KL Divergence: Optimal Minimax Rate. IEEE Trans. Inf. Theory 64 (4) (2018)
Yuheng Bu, Shaofeng Zou, Venugopal V. Veeravalli
Linear Complexity Exponentially Consistent Tests for Outlying Sequence Detection. CoRR (2017)
Yuheng Bu, Shaofeng Zou, Venugopal V. Veeravalli
Linear-complexity exponentially-consistent tests for universal outlying sequence detection. ISIT (2017)
Yuheng Bu, Shaofeng Zou, Yingbin Liang, Venugopal V. Veeravalli
Estimation of KL divergence between large-alphabet distributions. ISIT (2016)
Yuheng Bu, Shaofeng Zou, Yingbin Liang, Venugopal V. Veeravalli
Universal outlying sequence detection for continuous observations. ICASSP (2016)
Yuheng Bu, Shaofeng Zou, Yingbin Liang, Venugopal V. Veeravalli
Estimation of KL Divergence: Optimal Minimax Rate. CoRR (2016)
Yuheng Bu, Shaofeng Zou, Yingbin Liang, Venugopal V. Veeravalli
Universal Outlying sequence detection For Continuous Observations. CoRR (2015)