Bu, Yuheng

21 publications

TMLR 2025 Class-Wise Generalization Error: An Information-Theoretic Analysis Firas Laakom, Moncef Gabbouj, Jürgen Schmidhuber, Yuheng Bu

ICLRW 2025 Distributional Information Embedding: A Framework for Multi-Bit Watermarking Haiyun He, Yepeng Liu, Ziqiao Wang, Yongyi Mao, Yuheng Bu

ICML 2025 Fairness Overfitting in Machine Learning: An Information-Theoretic Perspective Firas Laakom, Haobo Chen, Jürgen Schmidhuber, Yuheng Bu

ICLR 2025 Image Watermarks Are Removable Using Controllable Regeneration from Clean Noise Yepeng Liu, Yiren Song, Hai Ci, Yu Zhang, Haofan Wang, Mike Zheng Shou, Yuheng Bu

NeurIPS 2025 Theoretically Grounded Framework for LLM Watermarking: A Distribution-Adaptive Approach Haiyun He, Yepeng Liu, Ziqiao Wang, Yongyi Mao, Yuheng Bu

ICLRW 2025 Theoretically Grounded Framework for LLM Watermarking: A Distribution-Adaptive Approach Haiyun He, Yepeng Liu, Ziqiao Wang, Yongyi Mao, Yuheng Bu

ICML 2024 Adaptive Text Watermark for Large Language Models Yepeng Liu, Yuheng Bu

NeurIPS 2024 Are Uncertainty Quantification Capabilities of Evidential Deep Learning a Mirage? Maohao Shen, J. Jon Ryu, Soumya Ghosh, Yuheng Bu, Prasanna Sattigeri, Subhro Das, Gregory W. Wornell

AISTATS 2024 Gibbs-Based Information Criteria and the Over-Parameterized Regime Haobo Chen, Gregory W Wornell, Yuheng Bu

IJCAI 2024 Information-Theoretic Opacity-Enforcement in Markov Decision Processes Chongyang Shi, Yuheng Bu, Jie Fu

ICML 2024 Operator SVD with Neural Networks via Nested Low-Rank Approximation Jongha Jon Ryu, Xiangxiang Xu, Hasan Sabri Melihcan Erol, Yuheng Bu, Lizhong Zheng, Gregory W. Wornell

NeurIPSW 2023 Gibbs-Based Information Criteria and the Over-Parameterized Regime Haobo Chen, Yuheng Bu, Gregory Wornell

AISTATS 2023 How Does Pseudo-Labeling Affect the Generalization Error of the Semi-Supervised Gibbs Algorithm? Haiyun He, Gholamali Aminian, Yuheng Bu, Miguel Rodrigues, Vincent Y. F. Tan

ICML 2023 On Balancing Bias and Variance in Unsupervised Multi-Source-Free Domain Adaptation Maohao Shen, Yuheng Bu, Gregory W. Wornell

AAAI 2023 Post-Hoc Uncertainty Learning Using a Dirichlet Meta-Model Maohao Shen, Yuheng Bu, Prasanna Sattigeri, Soumya Ghosh, Subhro Das, Gregory W. Wornell

NeurIPSW 2023 SAUC: Sparsity-Aware Uncertainty Calibration for Spatiotemporal Prediction with Graph Neural Networks Dingyi Zhuang, Yuheng Bu, Guang Wang, Shenhao Wang, Jinhua Zhao

AISTATS 2022 Characterizing and Understanding the Generalization Error of Transfer Learning with Gibbs Algorithm Yuheng Bu, Gholamali Aminian, Laura Toni, Gregory W. Wornell, Miguel Rodrigues

ICML 2022 Selective Regression Under Fairness Criteria Abhin Shah, Yuheng Bu, Joshua K Lee, Subhro Das, Rameswar Panda, Prasanna Sattigeri, Gregory W Wornell

NeurIPS 2021 An Exact Characterization of the Generalization Error for the Gibbs Algorithm Gholamali Aminian, Yuheng Bu, Laura Toni, Miguel Rodrigues, Gregory Wornell

ICML 2021 Fair Selective Classification via Sufficiency Joshua K Lee, Yuheng Bu, Deepta Rajan, Prasanna Sattigeri, Rameswar Panda, Subhro Das, Gregory W Wornell

AAAI 2020 Information-Theoretic Understanding of Population Risk Improvement with Model Compression Yuheng Bu, Weihao Gao, Shaofeng Zou, Venugopal V. Veeravalli