Bao, Han

40 publications

NeurIPS 2025 Any-Stepsize Gradient Descent for Separable Data Under Fenchel–Young Losses Han Bao, Shinsaku Sakaue, Yuki Takezawa

AISTATS 2025 Calm Composite Losses: Being Improper yet Proper Composite Han Bao, Nontawat Charoenphakdee

NeurIPS 2025 Establishing Linear Surrogate Regret Bounds for Convex Smooth Losses via Convolutional Fenchel–Young Losses Yuzhou Cao, Han Bao, Lei Feng, Bo An

ICML 2025 FlatQuant: Flatness Matters for LLM Quantization Yuxuan Sun, Ruikang Liu, Haoli Bai, Han Bao, Kang Zhao, Yuening Li, Jiaxin Hu, Xianzhi Yu, Lu Hou, Chun Yuan, Xin Jiang, Wulong Liu, Jun Yao

AISTATS 2025 Inverse Optimization with Prediction Market: A Characterization of Scoring Rules for Elciting System States Han Bao, Shinsaku Sakaue

AAAI 2025 LiD-FL: Towards List-Decodable Federated Learning Hong Liu, Liren Shan, Han Bao, Ronghui You, Yuhao Yi, Jiancheng Lv

TMLR 2025 Necessary and Sufficient Watermark for Large Language Models Yuki Takezawa, Ryoma Sato, Han Bao, Kenta Niwa, Makoto Yamada

NeurIPS 2025 Online Inverse Linear Optimization: Efficient Logarithmic-Regret Algorithm, Robustness to Suboptimality, and Lower Bound Shinsaku Sakaue, Taira Tsuchiya, Han Bao, Taihei Oki

ICLR 2025 PhiNets: Brain-Inspired Non-Contrastive Learning Based on Temporal Prediction Hypothesis Satoki Ishikawa, Makoto Yamada, Han Bao, Yuki Takezawa

AISTATS 2025 Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel–Young Loss Perspective and Gap-Dependent Regret Analysis Shinsaku Sakaue, Han Bao, Taira Tsuchiya

MLJ 2025 Scalable Individual Treatment Effect Estimator for Large Graphs Xiaofeng Lin, Han Bao, Yan Cui, Koh Takeuchi, Hisashi Kashima

ICLR 2025 TAID: Temporally Adaptive Interpolated Distillation for Efficient Knowledge Transfer in Language Models Makoto Shing, Kou Misaki, Han Bao, Sho Yokoi, Takuya Akiba

AISTATS 2024 Fast 1-Wasserstein Distance Approximations Using Greedy Strategies Guillaume Houry, Han Bao, Han Zhao, Makoto Yamada

COLT 2024 Online Structured Prediction with Fenchel–Young Losses and Improved Surrogate Regret for Online Multiclass Classification with Logistic Loss Shinsaku Sakaue, Han Bao, Taira Tsuchiya, Taihei Oki

NeurIPS 2024 Parameter-Free Clipped Gradient Descent Meets Polyak Yuki Takezawa, Han Bao, Ryoma Sato, Kenta Niwa, Makoto Yamada

IJCAI 2024 Pluggable Watermarking of Deepfake Models for Deepfake Detection Han Bao, Xuhong Zhang, Qinying Wang, Kangming Liang, Zonghui Wang, Shouling Ji, Wenzhi Chen

AAAI 2024 Referee-Meta-Learning for Fast Adaptation of Locational Fairness Weiye Chen, Yiqun Xie, Xiaowei Jia, Erhu He, Han Bao, Bang An, Xun Zhou

ICML 2024 Self-Attention Networks Localize When QK-Eigenspectrum Concentrates Han Bao, Ryuichiro Hataya, Ryo Karakida

NeurIPSW 2024 TAID: Temporally Adaptive Interpolated Distillation for Efficient Knowledge Transfer in Language Models Makoto Shing, Kou Misaki, Han Bao, Sho Yokoi, Takuya Akiba

NeurIPS 2024 Zipfian Whitening Sho Yokoi, Han Bao, Hiroto Kurita, Hidetoshi Shimodaira

AAAI 2023 Auto-CM: Unsupervised Deep Learning for Satellite Imagery Composition and Cloud Masking Using Spatio-Temporal Dynamics Yiqun Xie, Zhili Li, Han Bao, Xiaowei Jia, Dongkuan Xu, Xun Zhou, Sergii Skakun

AAAI 2023 BEVStereo: Enhancing Depth Estimation in Multi-View 3D Object Detection with Temporal Stereo Yinhao Li, Han Bao, Zheng Ge, Jinrong Yang, Jianjian Sun, Zeming Li

NeurIPS 2023 Beyond Exponential Graph: Communication-Efficient Topologies for Decentralized Learning via Finite-Time Convergence Yuki Takezawa, Ryoma Sato, Han Bao, Kenta Niwa, Makoto Yamada

ECML-PKDD 2023 Estimating Treatment Effects Under Heterogeneous Interference Xiaofeng Lin, Guoxi Zhang, Xiaotian Lu, Han Bao, Koh Takeuchi, Hisashi Kashima

TMLR 2023 Momentum Tracking: Momentum Acceleration for Decentralized Deep Learning on Heterogeneous Data Yuki Takezawa, Han Bao, Kenta Niwa, Ryoma Sato, Makoto Yamada

COLT 2023 Proper Losses, Moduli of Convexity, and Surrogate Regret Bounds Han Bao

ICCV 2023 Will Large-Scale Generative Models Corrupt Future Datasets? Ryuichiro Hataya, Han Bao, Hiromi Arai

AISTATS 2022 Pairwise Supervision Can Provably Elicit a Decision Boundary Han Bao, Takuya Shimada, Liyuan Xu, Issei Sato, Masashi Sugiyama

TMLR 2022 Approximating 1-Wasserstein Distance with Trees Makoto Yamada, Yuki Takezawa, Ryoma Sato, Han Bao, Zornitsa Kozareva, Sujith Ravi

AAAI 2022 Fairness by "Where": A Statistically-Robust and Model-Agnostic Bi-Level Learning Framework Yiqun Xie, Erhu He, Xiaowei Jia, Weiye Chen, Sergii Skakun, Han Bao, Zhe Jiang, Rahul Ghosh, Praveen Ravirathinam

ICML 2022 On the Surrogate Gap Between Contrastive and Supervised Losses Han Bao, Yoshihiro Nagano, Kento Nozawa

ACML 2022 Robust Computation of Optimal Transport by $β$-Potential Regularization Shintaro Nakamura, Han Bao, Masashi Sugiyama

IJCAI 2022 Statistically-Guided Deep Network Transformation to Harness Heterogeneity in Space (Extended Abstract) Yiqun Xie, Erhu He, Xiaowei Jia, Han Bao, Xun Zhou, Rahul Ghosh, Praveen Ravirathinam

AISTATS 2021 Fenchel-Young Losses with Skewed Entropies for Class-Posterior Probability Estimation Han Bao, Masashi Sugiyama

ECML-PKDD 2021 Learning from Noisy Similar and Dissimilar Data Soham Dan, Han Bao, Masashi Sugiyama

COLT 2020 Calibrated Surrogate Losses for Adversarially Robust Classification Han Bao, Clay Scott, Masashi Sugiyama

AISTATS 2020 Calibrated Surrogate Maximization of Linear-Fractional Utility in Binary Classification Han Bao, Masashi Sugiyama

ICML 2019 Imitation Learning from Imperfect Demonstration Yueh-Hua Wu, Nontawat Charoenphakdee, Han Bao, Voot Tangkaratt, Masashi Sugiyama

AAAI 2019 Unsupervised Domain Adaptation Based on Source-Guided Discrepancy Seiichi Kuroki, Nontawat Charoenphakdee, Han Bao, Junya Honda, Issei Sato, Masashi Sugiyama

ICML 2018 Classification from Pairwise Similarity and Unlabeled Data Han Bao, Gang Niu, Masashi Sugiyama