Han Zhao

ORCID

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 125

Top Venues

Publications

Xiaotian Han, Jianfeng Chi, Yu Chen, Qifan Wang, Han Zhao, Na Zou, Xia Hu
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods. ICLR (2024)
Ziyu Gong, Ben Usman, Han Zhao, David I. Inouye
Towards Practical Non-Adversarial Distribution Matching. AISTATS (2024)
Han Zhao
Fair and Optimal Prediction via Post-Processing. AAAI (2024)
Yifei He, Shiji Zhou, Guojun Zhang, Hyokun Yun, Yi Xu, Belinda Zeng, Trishul Chilimbi, Han Zhao
Robust Multi-Task Learning with Excess Risks. CoRR (2024)
Haoxiang Wang, Wei Xiong, Tengyang Xie, Han Zhao, Tong Zhang
Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts. CoRR (2024)
Haoxiang Wang, Haozhe Si, Huajie Shao, Han Zhao
Enhancing Compositional Generalization via Compositional Feature Alignment. Trans. Mach. Learn. Res. 2024 (2024)
Xiaoyang Wang, Han Zhao, Klara Nahrstedt, Sanmi Koyejo
Personalized Federated Learning with Spurious Features: An Adversarial Approach. Trans. Mach. Learn. Res. 2024 (2024)
Haoxiang Wang, Haozhe Si, Huajie Shao, Han Zhao
Enhancing Compositional Generalization via Compositional Feature Alignment. CoRR (2024)
Guillaume Houry, Han Bao, Han Zhao, Makoto Yamada
Fast 1-Wasserstein distance approximations using greedy strategies. AISTATS (2024)
Ruicheng Xian, Han Zhao
Optimal Group Fair Classifiers from Linear Post-Processing. CoRR (2024)
Shikun Liu, Deyu Zou, Han Zhao, Pan Li
Pairwise Alignment Improves Graph Domain Adaptation. CoRR (2024)
Ruicheng Xian, Qiaobo Li, Gautam Kamath, Han Zhao
Differentially Private Post-Processing for Fair Regression. CoRR (2024)
Viet Duong, Qiong Wu, Zhengyi Zhou, Eric Zavesky, Wen-Ling Hsu, Han Zhao, Huajie Shao
A General-Purpose Multi-Modal OOD Detection Framework. Trans. Mach. Learn. Res. 2024 (2024)
Hanze Dong, Wei Xiong, Bo Pang, Haoxiang Wang, Han Zhao, Yingbo Zhou, Nan Jiang, Doyen Sahoo, Caiming Xiong, Tong Zhang
RLHF Workflow: From Reward Modeling to Online RLHF. CoRR (2024)
Yifan Yang, Mingquan Lin, Han Zhao, Yifan Peng, Furong Huang, Zhiyong Lu
A survey of recent methods for addressing AI fairness and bias in biomedicine. J. Biomed. Informatics 154 (2024)
Haoxiang Wang, Yong Lin, Wei Xiong, Rui Yang, Shizhe Diao, Shuang Qiu, Han Zhao, Tong Zhang
Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewards. CoRR (2024)
Makoto Yamada, Yuki Takezawa, Guillaume Houry, Kira Michaela Dusterwald, Déborah Sulem, Han Zhao, Yao-Hung Hubert Tsai
An Empirical Study of Simplicial Representation Learning with Wasserstein Distance. CoRR (2023)
Costas Mavromatis, Vassilis N. Ioannidis, Shen Wang, Da Zheng, Soji Adeshina, Jun Ma, Han Zhao, Christos Faloutsos, George Karypis
Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphs. ECML/PKDD (3) (2023)
Yong Lin, Lu Tan, Hangyu Lin, Zeming Zheng, Renjie Pi, Jipeng Zhang, Shizhe Diao, Haoxiang Wang, Han Zhao, Yuan Yao, Tong Zhang
Speciality vs Generality: An Empirical Study on Catastrophic Forgetting in Fine-tuning Foundation Models. CoRR (2023)
Costas Mavromatis, Vassilis N. Ioannidis, Shen Wang, Da Zheng, Soji Adeshina, Jun Ma, Han Zhao, Christos Faloutsos, George Karypis
Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphs. CoRR (2023)
Zikun Chen, Han Zhao, Parham Aarabi, Ruowei Jiang
SC2GAN: Rethinking Entanglement by Self-correcting Correlated GAN Space. CoRR (2023)
Ruicheng Xian, Honglei Zhuang, Zhen Qin, Hamed Zamani, Jing Lu, Ji Ma, Kai Hui, Han Zhao, Xuanhui Wang, Michael Bendersky
Learning List-Level Domain-Invariant Representations for Ranking. NeurIPS (2023)
Haoxiang Wang, Gargi Balasubramaniam, Haozhe Si, Bo Li, Han Zhao
Invariant-Feature Subspace Recovery: A New Class of Provable Domain Generalization Algorithms. CoRR (2023)
Jian Shen, Hang Lai, Minghuan Liu, Han Zhao, Yong Yu, Weinan Zhang
Adaptation Augmented Model-based Policy Optimization. J. Mach. Learn. Res. 24 (2023)
Zikun Chen, Han Zhao, Parham Aarabi, Ruowei Jiang
GAN: Rethinking Entanglement by Self-correcting Correlated GAN Space. ICCV (Workshops) (2023)
Yuzheng Hu, Ruicheng Xian, Qilong Wu, Qiuling Fan, Lang Yin, Han Zhao
Revisiting Scalarization in Multi-Task Learning: A Theoretical Perspective. CoRR (2023)
Ruicheng Xian, Lang Yin, Han Zhao
Fair and Optimal Classification via Post-Processing. ICML (2023)
Shikun Liu, Tianchun Li, Yongbin Feng, Nhan Tran, Han Zhao, Qiang Qiu, Pan Li
Structural Re-weighting Improves Graph Domain Adaptation. ICML (2023)
Qian Jiang, Changyou Chen, Han Zhao, Liqun Chen, Qing Ping, Son Dinh Tran, Yi Xu, Belinda Zeng, Trishul Chilimbi
Understanding and Constructing Latent Modality Structures in Multi-Modal Representation Learning. CVPR (2023)
Siqi Zeng, Remi Tachet des Combes, Han Zhao
Learning Structured Representations by Embedding Class Hierarchy. ICLR (2023)
Yifei He, Haoxiang Wang, Bo Li, Han Zhao
Gradual Domain Adaptation: Theory and Algorithms. CoRR (2023)
Yuzheng Hu, Ruicheng Xian, Qilong Wu, Qiuling Fan, Lang Yin, Han Zhao
Revisiting Scalarization in Multi-Task Learning: A Theoretical Perspective. NeurIPS (2023)
Bowen Jin, Wentao Zhang, Yu Zhang, Yu Meng, Han Zhao, Jiawei Han
Learning Multiplex Embeddings on Text-rich Networks with One Text Encoder. CoRR (2023)
Seiyun Shin, Ilan Shomorony, Han Zhao
Efficient Learning of Linear Graph Neural Networks via Node Subsampling. NeurIPS (2023)
Yuzheng Hu, Fan Wu, Hongyang Zhang, Han Zhao
Understanding the Impact of Adversarial Robustness on Accuracy Disparity. ICML (2023)
Runxiang Cheng, Gargi Balasubramaniam, Yifei He, Yao-Hung Hubert Tsai, Han Zhao
Greedy Modality Selection via Approximate Submodular Maximization. CoRR (2022)
Wenda Chu, Chulin Xie, Boxin Wang, Linyi Li, Lang Yin, Han Zhao, Bo Li
FOCUS: Fairness via Agent-Awareness for Federated Learning on Heterogeneous Data. CoRR (2022)
Jing Dong, Shiji Zhou, Baoxiang Wang, Han Zhao
Algorithms and Theory for Supervised Gradual Domain Adaptation. Trans. Mach. Learn. Res. 2022 (2022)
Bo Li, Yifei Shen, Yezhen Wang, Wenzhen Zhu, Colorado Reed, Dongsheng Li, Kurt Keutzer, Han Zhao
Invariant Information Bottleneck for Domain Generalization. AAAI (2022)
Ruicheng Xian, Honglei Zhuang, Zhen Qin, Hamed Zamani, Jing Lu, Ji Ma, Kai Hui, Han Zhao, Xuanhui Wang, Michael Bendersky
Learning List-Level Domain-Invariant Representations for Ranking. CoRR (2022)
Zhenhailong Wang, Hang Yu, Manling Li, Han Zhao, Heng Ji
Model-Agnostic Multitask Fine-tuning for Few-shot Vision-Language Transfer Learning. CoRR (2022)
Jing Dong, Shiji Zhou, Baoxiang Wang, Han Zhao
Algorithms and Theory for Supervised Gradual Domain Adaptation. CoRR (2022)
Han Zhao, Geoffrey J. Gordon
Inherent Tradeoffs in Learning Fair Representations. J. Mach. Learn. Res. 23 (2022)
Yuzheng Hu, Fan Wu, Hongyang Zhang, Han Zhao
Understanding the Impact of Adversarial Robustness on Accuracy Disparity. CoRR (2022)
Ruicheng Xian, Heng Ji, Han Zhao
Cross-Lingual Transfer with Class-Weighted Language-Invariant Representations. ICLR (2022)
Haoxiang Wang, Haozhe Si, Bo Li, Han Zhao
Provable Domain Generalization via Invariant-Feature Subspace Recovery. CoRR (2022)
Han Zhao, Chen Dan, Bryon Aragam, Tommi S. Jaakkola, Geoffrey J. Gordon, Pradeep Ravikumar
Fundamental Limits and Tradeoffs in Invariant Representation Learning. J. Mach. Learn. Res. 23 (2022)
Runxiang Cheng, Gargi Balasubramaniam, Yifei He, Yao-Hung Hubert Tsai, Han Zhao
Greedy modality selection via approximate submodular maximization. UAI (2022)
Sicheng Zhao, Xiangyu Yue, Shanghang Zhang, Bo Li, Han Zhao, Bichen Wu, Ravi Krishna, Joseph E. Gonzalez, Alberto L. Sangiovanni-Vincentelli, Sanjit A. Seshia, Kurt Keutzer
A Review of Single-Source Deep Unsupervised Visual Domain Adaptation. IEEE Trans. Neural Networks Learn. Syst. 33 (2) (2022)
Yao-Hung Hubert Tsai, Tianqin Li, Martin Q. Ma, Han Zhao, Kun Zhang, Louis-Philippe Morency, Ruslan Salakhutdinov
Conditional Contrastive Learning with Kernel. CoRR (2022)
Shiji Zhou, Han Zhao, Shanghang Zhang, Lianzhe Wang, Heng Chang, Zhi Wang, Wenwu Zhu
Online Continual Adaptation with Active Self-Training. AISTATS (2022)
Ruicheng Xian, Lang Yin, Han Zhao
Fair and Optimal Classification via Transports to Wasserstein-Barycenter. CoRR (2022)
Jianfeng Chi, William Shand, Yaodong Yu, Kai-Wei Chang, Han Zhao, Yuan Tian
Conditional Supervised Contrastive Learning for Fair Text Classification. CoRR (2022)
Jianfeng Chi, Jian Shen, Xinyi Dai, Weinan Zhang, Yuan Tian, Han Zhao
Towards Return Parity in Markov Decision Processes. AISTATS (2022)
Haoxiang Wang, Bo Li, Han Zhao
Understanding Gradual Domain Adaptation: Improved Analysis, Optimal Path and Beyond. ICML (2022)
Jianfeng Chi, William Shand, Yaodong Yu, Kai-Wei Chang, Han Zhao, Yuan Tian
Conditional Supervised Contrastive Learning for Fair Text Classification. EMNLP (Findings) (2022)
Yao-Hung Hubert Tsai, Tianqin Li, Martin Q. Ma, Han Zhao, Kun Zhang, Louis-Philippe Morency, Ruslan Salakhutdinov
Conditional Contrastive Learning with Kernel. ICLR (2022)
Haoxiang Wang, Bo Li, Han Zhao
Understanding Gradual Domain Adaptation: Improved Analysis, Optimal Path and Beyond. CoRR (2022)
Haoxiang Wang, Haozhe Si, Bo Li, Han Zhao
Provable Domain Generalization via Invariant-Feature Subspace Recovery. ICML (2022)
Guojun Zhang, Han Zhao, Yaoliang Yu, Pascal Poupart
Quantifying and Improving Transferability in Domain Generalization. NeurIPS (2021)
Bo Li, Yezhen Wang, Shanghang Zhang, Dongsheng Li, Kurt Keutzer, Trevor Darrell, Han Zhao
Learning Invariant Representations and Risks for Semi-Supervised Domain Adaptation. CVPR (2021)
Jianfeng Chi, Jian Shen, Xinyi Dai, Weinan Zhang, Yuan Tian, Han Zhao
Towards Return Parity in Markov Decision Processes. CoRR (2021)
Yao-Hung Hubert Tsai, Martin Q. Ma, Han Zhao, Kun Zhang, Louis-Philippe Morency, Ruslan Salakhutdinov
Conditional Contrastive Learning: Removing Undesirable Information in Self-Supervised Representations. CoRR (2021)
Han Zhao
Costs and Benefits of Wasserstein Fair Regression. CoRR (2021)
Shiji Zhou, Han Zhao, Shanghang Zhang, Lianzhe Wang, Heng Chang, Zhi Wang, Wenwu Zhu
Online Continual Adaptation with Active Self-Training. CoRR (2021)
Haoxiang Wang, Han Zhao, Bo Li
Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation. CoRR (2021)
Guojun Zhang, Han Zhao, Yaoliang Yu, Pascal Poupart
Quantifying and Improving Transferability in Domain Generalization. CoRR (2021)
Yao-Hung Hubert Tsai, Martin Q. Ma, Muqiao Yang, Han Zhao, Louis-Philippe Morency, Ruslan Salakhutdinov
Self-supervised Representation Learning with Relative Predictive Coding. ICLR (2021)
Peizhao Li, Yifei Wang, Han Zhao, Pengyu Hong, Hongfu Liu
On Dyadic Fairness: Exploring and Mitigating Bias in Graph Connections. ICLR (2021)
Bo Li, Yifei Shen, Yezhen Wang, Wenzhen Zhu, Colorado J. Reed, Jun Zhang, Dongsheng Li, Kurt Keutzer, Han Zhao
Invariant Information Bottleneck for Domain Generalization. CoRR (2021)
Haoxiang Wang, Han Zhao, Bo Li
Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation. ICML (2021)
Jianfeng Chi, Yuan Tian, Geoffrey J. Gordon, Han Zhao
Understanding and Mitigating Accuracy Disparity in Regression. ICML (2021)
Peiyuan Liao, Han Zhao, Keyulu Xu, Tommi S. Jaakkola, Geoffrey J. Gordon, Stefanie Jegelka, Ruslan Salakhutdinov
Information Obfuscation of Graph Neural Networks. ICML (2021)
Jianfeng Chi, Yuan Tian, Geoffrey J. Gordon, Han Zhao
Understanding and Mitigating Accuracy Disparity in Regression. CoRR (2021)
Yao-Hung Hubert Tsai, Martin Q. Ma, Muqiao Yang, Han Zhao, Louis-Philippe Morency, Ruslan Salakhutdinov
Self-supervised Representation Learning with Relative Predictive Coding. CoRR (2021)
Peiyuan Liao, Han Zhao, Keyulu Xu, Tommi S. Jaakkola, Geoffrey J. Gordon, Stefanie Jegelka, Ruslan Salakhutdinov
Graph Adversarial Networks: Protecting Information against Adversarial Attacks. CoRR (2020)
Remi Tachet des Combes, Han Zhao, Yu-Xiang Wang, Geoffrey J. Gordon
Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift. CoRR (2020)
Yao-Hung Hubert Tsai, Han Zhao, Makoto Yamada, Louis-Philippe Morency, Russ R. Salakhutdinov
Neural Methods for Point-wise Dependency Estimation. NeurIPS (2020)
Han Zhao, Chen Dan, Bryon Aragam, Tommi S. Jaakkola, Geoffrey J. Gordon, Pradeep Ravikumar
Fundamental Limits and Tradeoffs in Invariant Representation Learning. CoRR (2020)
Tameem Adel, Han Zhao, Richard E. Turner
Continual Learning with Adaptive Weights (CLAW). ICLR (2020)
Han Zhao, Junjie Hu, Andrej Risteski
On Learning Language-Invariant Representations for Universal Machine Translation. CoRR (2020)
Wen Wang, Han Zhao, Honglei Zhuang, Nirav Shah, Rema Padman
DyCRS: Dynamic Interpretable Postoperative Complication Risk Scoring. WWW (2020)
Han Zhao, Junjie Hu, Andrej Risteski
On Learning Language-Invariant Representations for Universal Machine Translation. ICML (2020)
Peizhao Li, Han Zhao, Hongfu Liu
Deep Fair Clustering for Visual Learning. CVPR (2020)
Han Zhao, Jianfeng Chi, Yuan Tian, Geoffrey J. Gordon
Trade-offs and Guarantees of Adversarial Representation Learning for Information Obfuscation. NeurIPS (2020)
Jian Shen, Han Zhao, Weinan Zhang, Yong Yu
Model-based Policy Optimization with Unsupervised Model Adaptation. CoRR (2020)
Remi Tachet des Combes, Han Zhao, Yu-Xiang Wang, Geoffrey J. Gordon
Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift. NeurIPS (2020)
Han Zhao, Amanda Coston, Tameem Adel, Geoffrey J. Gordon
Conditional Learning of Fair Representations. ICLR (2020)
Sicheng Zhao, Xiangyu Yue, Shanghang Zhang, Bo Li, Han Zhao, Bichen Wu, Ravi Krishna, Joseph E. Gonzalez, Alberto L. Sangiovanni-Vincentelli, Sanjit A. Seshia, Kurt Keutzer
A Review of Single-Source Deep Unsupervised Visual Domain Adaptation. CoRR (2020)
Jian Shen, Han Zhao, Weinan Zhang, Yong Yu
Model-based Policy Optimization with Unsupervised Model Adaptation. NeurIPS (2020)
Bo Li, Yezhen Wang, Shanghang Zhang, Dongsheng Li, Trevor Darrell, Kurt Keutzer, Han Zhao
Learning Invariant Representations and Risks for Semi-supervised Domain Adaptation. CoRR (2020)
Yao-Hung Hubert Tsai, Han Zhao, Makoto Yamada, Louis-Philippe Morency, Ruslan Salakhutdinov
Neural Methods for Point-wise Dependency Estimation. CoRR (2020)
Han Zhao, Otilia Stretcu, Alexander J. Smola, Geoffrey J. Gordon
Efficient Multitask Feature and Relationship Learning. UAI (2019)
Han Zhao, Geoffrey J. Gordon
Inherent Tradeoffs in Learning Fair Representation. CoRR (2019)
Han Zhao, Yao-Hung Hubert Tsai, Ruslan Salakhutdinov, Geoffrey J. Gordon
Learning Neural Networks with Adaptive Regularization. CoRR (2019)
Han Zhao, Jianfeng Chi, Yuan Tian, Geoffrey J. Gordon
Adversarial Task-Specific Privacy Preservation under Attribute Attack. CoRR (2019)
Yichong Xu, Han Zhao, Xiaofei Shi, Nihar B. Shah
On Strategyproof Conference Peer Review. IJCAI (2019)
Han Zhao, Amanda Coston, Tameem Adel, Geoffrey J. Gordon
Conditional Learning of Fair Representations. CoRR (2019)
Tameem Adel, Han Zhao, Richard E. Turner
Continual Learning with Adaptive Weights (CLAW). CoRR (2019)
Han Zhao, Geoffrey J. Gordon
Inherent Tradeoffs in Learning Fair Representations. NeurIPS (2019)

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Publication Activity (10 Years)

Top Topics

Top Venues

Han Zhao