Han Zhao

212 papers A* 56A 11B 2Misc 1Journal 124Unranked 17
YearRankTypeTitle / Venue / Authors
2026 J jnl
A Unified Theory of Random Projection for Influence Functions.
CoRR
Pingbang Hu, Yuzheng Hu, Jiaqi W. Ma, Han Zhao
2026 J jnl
Adaptive Online Mirror Descent for Tchebycheff Scalarization in Multi-Objective Learning.
Trans. Mach. Learn. Res.
Meitong Liu, Xiaoyuan Zhang, Chulin Xie, Kate Donahue, Han Zhao
2026 J jnl
Weakly-Supervised Disentangled Representation Learning via Filter-Based Adaptive Swapping.
Trans. Mach. Learn. Res.
Zhenyu Zong, Qidi Wang, Simon Yu, Hongpeng Cao, Yanbing Mao, Han Zhao, Lui Sha, Huajie Shao
2025 J jnl
A Snapshot of Influence: A Local Data Attribution Framework for Online Reinforcement Learning.
CoRR
Yuzheng Hu, Fan Wu, Haotian Ye, David A. Forsyth, James Zou, Nan Jiang, Jiaqi W. Ma, Han Zhao
2025 J jnl
ACTG-ARL: Differentially Private Conditional Text Generation with RL-Boosted Control.
CoRR
Yuzheng Hu, Ryan McKenna, Da Yu, Shanshan Wu, Han Zhao, Zheng Xu, Peter Kairouz
2025 A* conf
Accelerating Neural ODEs: A Variational Formulation-based Approach.
ICLR
Hongjue Zhao, Yuchen Wang, Hairong Qi, Zijie Huang, Han Zhao, Lui Sha, Huajie Shao
2025 J jnl
Efficient Model Editing with Task Vector Bases: A Theoretical Framework and Scalable Approach.
CoRR
Siqi Zeng, Yifei He, Weiqiu You, Yifan Hao, Yao-Hung Hubert Tsai, Makoto Yamada, Han Zhao
2025 J jnl
Efficient Utility-Preserving Machine Unlearning with Implicit Gradient Surgery.
CoRR
Shiji Zhou, Tianbai Yu, Zhi Zhang, Heng Chang, Xiao Zhou, Dong Wu, Han Zhao
2025 J jnl
GraSS: Scalable Influence Function with Sparse Gradient Compression.
CoRR
Pingbang Hu, Joseph Melkonian, Weijing Tang, Han Zhao, Jiaqi W. Ma
2025 J jnl
Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond.
CoRR
Weiyu Chen, Xiaoyuan Zhang, Baijiong Lin, Xi Lin, Han Zhao, Qingfu Zhang, James T. Kwok
2025 J jnl
Group Fairness Meets the Black Box: Enabling Fair Algorithms on Closed LLMs via Post-Processing.
CoRR
Ruicheng Xian, Yuxuan Wan, Han Zhao
2025 A* conf
Learning Structured Representations by Embedding Class Hierarchy with Fast Optimal Transport.
ICLR
Siqi Zeng, Sixian Du, Makoto Yamada, Han Zhao
2025 J jnl
Localize-and-Stitch: Efficient Model Merging via Sparse Task Arithmetic.
Trans. Mach. Learn. Res.
Yifei He, Yuzheng Hu, Yong Lin, Tong Zhang, Han Zhao
2025 J jnl
MergeBench: A Benchmark for Merging Domain-Specialized LLMs.
CoRR
Yifei He, Siqi Zeng, Yuzheng Hu, Rui Yang, Tong Zhang, Han Zhao
2025 A* conf
MiCRo: Mixture Modeling and Context-aware Routing for Personalized Preference Learning.
EMNLP
Jingyan Shen, Jiarui Yao, Rui Yang, Yifan Sun, Feng Luo, Rui Pan, Tong Zhang, Han Zhao
2025 J jnl
MiCRo: Mixture Modeling and Context-aware Routing for Personalized Preference Learning.
CoRR
Jingyan Shen, Jiarui Yao, Rui Yang, Yifan Sun, Feng Luo, Rui Pan, Tong Zhang, Han Zhao
2025 A conf
Moment Alignment: Unifying Gradient and Hessian Matching for Domain Generalization.
UAI
Yuen Chen, Haozhe Si, Guojun Zhang, Han Zhao
2025 J jnl
Moment Alignment: Unifying Gradient and Hessian Matching for Domain Generalization.
CoRR
Yuen Chen, Haozhe Si, Guojun Zhang, Han Zhao
2025 A* conf
Multiobjective distribution matching.
ICML
Xiaoyuan Zhang, Peijie Li, Yingying Yu, Yichi Zhang, Han Zhao, Qingfu Zhang
2025 J jnl
Neural Probabilistic Circuits: Enabling Compositional and Interpretable Predictions through Logical Reasoning.
CoRR
Weixin Chen, Simon Yu, Huajie Shao, Lui Sha, Han Zhao
2025 J jnl
S
CoRR
Xudong Liu, Zikun Chen, Ruowei Jiang, Ziyi Wu, Kejia Yin, Han Zhao, Parham Aarabi, Igor Gilitschenski
2025 — conf
Scaling Laws for Multilingual Language Models.
ACL (Findings)
Yifei He, Alon Benhaim, Barun Patra, Praneetha Vaddamanu, Sanchit Ahuja, Parul Chopra, Vishrav Chaudhary, Han Zhao, Xia Song
2025 J jnl
Structural Alignment Improves Graph Test-Time Adaptation.
CoRR
Hans Hao-Hsun Hsu, Shikun Liu, Han Zhao, Pan Li
2025 J jnl
Taming Hyperparameter Sensitivity in Data Attribution: Practical Selection Without Costly Retraining.
CoRR
Weiyi Wang, Junwei Deng, Yuzheng Hu, Shiyuan Zhang, Xirui Jiang, Runting Zhang, Han Zhao, Jiaqi W. Ma
2025 J jnl
Towards Scalable Foundation Model for Multi-modal and Hyperspectral Geospatial Data.
CoRR
Haozhe Si, Yuxuan Wan, Minh Do, Deepak Vasisht, Han Zhao, Hendrik F. Hamann
2025 — conf
Towards Understanding the Fragility of Multilingual LLMs against Fine-Tuning Attacks.
NAACL (Findings)
Samuele Poppi, Zheng-Xin Yong, Yifei He, Bobbie Chern, Han Zhao, Aobo Yang, Jianfeng Chi
2025 J jnl
Understanding Emergent In-Context Learning from a Kernel Regression Perspective.
Trans. Mach. Learn. Res.
Chi Han, Ziqi Wang, Han Zhao, Heng Ji
2025 J jnl
Understanding and Improving Adversarial Robustness of Neural Probabilistic Circuits.
CoRR
Weixin Chen, Han Zhao
2025 J jnl
VISAT: Benchmarking Adversarial and Distribution Shift Robustness in Traffic Sign Recognition with Visual Attributes.
CoRR
Simon Yu, Peilin Yu, Hongbo Zheng, Huajie Shao, Han Zhao, Lui Sha
2025 J jnl
When LRP Diverges from Leave-One-Out in Transformers.
CoRR
Weiqiu You, Siqi Zeng, Yao-Hung Hubert Tsai, Makoto Yamada, Han Zhao
2024 J jnl
A General-Purpose Multi-Modal OOD Detection Framework.
Trans. Mach. Learn. Res.
Viet Duong, Qiong Wu, Zhengyi Zhou, Eric Zavesky, Wen-Ling Hsu, Han Zhao, Huajie Shao
2024 J jnl
A survey of recent methods for addressing AI fairness and bias in biomedicine.
CoRR
Yifan Yang, Mingquan Lin, Han Zhao, Yifan Peng, Furong Huang, Zhiyong Lu
2024 J jnl
A survey of recent methods for addressing AI fairness and bias in biomedicine.
J. Biomed. Informatics
Yifan Yang, Mingquan Lin, Han Zhao, Yifan Peng, Furong Huang, Zhiyong Lu
2024 J jnl
An Empirical Study of Self-Supervised Learning with Wasserstein Distance.
Entropy
Makoto Yamada, Yuki Takezawa, Guillaume Houry, Kira Michaela Düsterwald, Déborah Sulem, Han Zhao, Yao-hung Tsai
2024 — conf
Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewards.
ACL (1)
Haoxiang Wang, Yong Lin, Wei Xiong, Rui Yang, Shizhe Diao, Shuang Qiu, Han Zhao, Tong Zhang
2024 J jnl
Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewards.
CoRR
Haoxiang Wang, Yong Lin, Wei Xiong, Rui Yang, Shizhe Diao, Shuang Qiu, Han Zhao, Tong Zhang
2024 A* conf
Differentially Private Post-Processing for Fair Regression.
ICML
Ruicheng Xian, Qiaobo Li, Gautam Kamath, Han Zhao
2024 J jnl
Differentially Private Post-Processing for Fair Regression.
CoRR
Ruicheng Xian, Qiaobo Li, Gautam Kamath, Han Zhao
2024 J jnl
Efficient Modality Selection in Multimodal Learning.
J. Mach. Learn. Res.
Yifei He, Runxiang Cheng, Gargi Balasubramaniam, Yao-Hung Hubert Tsai, Han Zhao
2024 J jnl
Enhancing Compositional Generalization via Compositional Feature Alignment.
CoRR
Haoxiang Wang, Haozhe Si, Huajie Shao, Han Zhao
2024 J jnl
Enhancing Compositional Generalization via Compositional Feature Alignment.
Trans. Mach. Learn. Res.
Haoxiang Wang, Haozhe Si, Huajie Shao, Han Zhao
2024 A* conf
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods.
ICLR
Xiaotian Han, Jianfeng Chi, Yu Chen, Qifan Wang, Han Zhao, Na Zou, Xia Hu
2024 A* conf
Fair and Optimal Prediction via Post-Processing.
AAAI
Han Zhao
2024 J jnl
Fair and optimal prediction via post-processing.
AI Mag.
Han Zhao
2024 A conf
Fast 1-Wasserstein distance approximations using greedy strategies.
AISTATS
Guillaume Houry, Han Bao, Han Zhao, Makoto Yamada
2024 A* conf
FedGTST: Boosting Global Transferability of Federated Models via Statistics Tuning.
NeurIPS
Evelyn Ma, Chao Pan, S. Rasoul Etesami, Han Zhao, Olgica Milenkovic
2024 J jnl
FedGTST: Boosting Global Transferability of Federated Models via Statistics Tuning.
CoRR
Evelyn Ma, Chao Pan, S. Rasoul Etesami, Han Zhao, Olgica Milenkovic
2024 J jnl
Gradual Domain Adaptation: Theory and Algorithms.
J. Mach. Learn. Res.
Yifei He, Haoxiang Wang, Bo Li, Han Zhao
2024 — conf
Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts.
EMNLP (Findings)
Haoxiang Wang, Wei Xiong, Tengyang Xie, Han Zhao, Tong Zhang
2024 J jnl
Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts.
CoRR
Haoxiang Wang, Wei Xiong, Tengyang Xie, Han Zhao, Tong Zhang
2024 J jnl
Learning Structured Representations by Embedding Class Hierarchy with Fast Optimal Transport.
CoRR
Siqi Zeng, Sixian Du, Makoto Yamada, Han Zhao
2024 A* conf
Learning Structured Representations with Hyperbolic Embeddings.
NeurIPS
Aditya Sinha, Siqi Zeng, Makoto Yamada, Han Zhao
2024 J jnl
Learning Structured Representations with Hyperbolic Embeddings.
CoRR
Aditya Sinha, Siqi Zeng, Makoto Yamada, Han Zhao
2024 A* conf
LibMOON: A Gradient-based MultiObjective OptimizatioN Library in PyTorch.
NeurIPS
Xiaoyuan Zhang, Liang Zhao, Yingying Yu, Xi Lin, Yifan Chen, Han Zhao, Qingfu Zhang
2024 J jnl
LibMOON: A Gradient-based MultiObjective OptimizatioN Library in PyTorch.
CoRR
Xiaoyuan Zhang, Liang Zhao, Yingying Yu, Xi Lin, Zhenkun Wang, Han Zhao, Qingfu Zhang
2024 J jnl
Localize-and-Stitch: Efficient Model Merging via Sparse Task Arithmetic.
CoRR
Yifei He, Yuzheng Hu, Yong Lin, Tong Zhang, Han Zhao
2024 A* conf
Mitigating the Alignment Tax of RLHF.
EMNLP
Yong Lin, Hangyu Lin, Wei Xiong, Shizhe Diao, Jianmeng Liu, Jipeng Zhang, Rui Pan, Haoxiang Wang, Wenbin Hu, Hanning Zhang, Hanze Dong, Renjie Pi, Han Zhao, Nan Jiang, Heng Ji, Yuan Yao, Tong Zhang
2024 A* conf
Most Influential Subset Selection: Challenges, Promises, and Beyond.
NeurIPS
Yuzheng Hu, Pingbang Hu, Han Zhao, Jiaqi W. Ma
2024 J jnl
Most Influential Subset Selection: Challenges, Promises, and Beyond.
CoRR
Yuzheng Hu, Pingbang Hu, Han Zhao, Jiaqi W. Ma
2024 A* conf
On the Expressive Power of Tree-Structured Probabilistic Circuits.
NeurIPS
Lang Yin, Han Zhao
2024 J jnl
On the Expressive Power of Tree-Structured Probabilistic Circuits.
CoRR
Lang Yin, Han Zhao
2024 J jnl
Online Mirror Descent for Tchebycheff Scalarization in Multi-Objective Optimization.
CoRR
Meitong Liu, Xiaoyuan Zhang, Chulin Xie, Kate Donahue, Han Zhao
2024 J jnl
Optimal Group Fair Classifiers from Linear Post-Processing.
CoRR
Ruicheng Xian, Han Zhao
2024 A* conf
Pairwise Alignment Improves Graph Domain Adaptation.
ICML
Shikun Liu, Deyu Zou, Han Zhao, Pan Li
2024 J jnl
Pairwise Alignment Improves Graph Domain Adaptation.
CoRR
Shikun Liu, Deyu Zou, Han Zhao, Pan Li
2024 J jnl
Personalized Federated Learning with Spurious Features: An Adversarial Approach.
Trans. Mach. Learn. Res.
Xiaoyang Wang, Han Zhao, Klara Nahrstedt, Sanmi Koyejo
2024 J jnl
RLHF Workflow: From Reward Modeling to Online RLHF.
CoRR
Hanze Dong, Wei Xiong, Bo Pang, Haoxiang Wang, Han Zhao, Yingbo Zhou, Nan Jiang, Doyen Sahoo, Caiming Xiong, Tong Zhang
2024 J jnl
RLHF Workflow: From Reward Modeling to Online RLHF.
Trans. Mach. Learn. Res.
Hanze Dong, Wei Xiong, Bo Pang, Haoxiang Wang, Han Zhao, Yingbo Zhou, Nan Jiang, Doyen Sahoo, Caiming Xiong, Tong Zhang
2024 A* conf
Robust Multi-Task Learning with Excess Risks.
ICML
Yifei He, Shiji Zhou, Guojun Zhang, Hyokun Yun, Yi Xu, Belinda Zeng, Trishul Chilimbi, Han Zhao
2024 J jnl
Robust Multi-Task Learning with Excess Risks.
CoRR
Yifei He, Shiji Zhou, Guojun Zhang, Hyokun Yun, Yi Xu, Belinda Zeng, Trishul Chilimbi, Han Zhao
2024 J jnl
S4: Self-Supervised Sensing Across the Spectrum.
CoRR
Jayanth Shenoy, Xingjian Davis Zhang, Shlok Mehrotra, Bill Tao, Rem Yang, Han Zhao, Deepak Vasisht
2024 J jnl
Scaling Laws for Multilingual Language Models.
CoRR
Yifei He, Alon Benhaim, Barun Patra, Praneetha Vaddamanu, Sanchit Ahuja, Parul Chopra, Vishrav Chaudhary, Han Zhao, Xia Song
2024 J jnl
Self-Supervised Learning across the Spectrum.
Remote. Sens.
Jayanth Shenoy, Xingjian Davis Zhang, Bill Tao, Shlok Mehrotra, Rem Yang, Han Zhao, Deepak Vasisht
2024 — conf
Semi-Supervised Reward Modeling via Iterative Self-Training.
EMNLP (Findings)
Yifei He, Haoxiang Wang, Ziyan Jiang, Alexandros Papangelis, Han Zhao
2024 J jnl
Semi-Supervised Reward Modeling via Iterative Self-Training.
CoRR
Yifei He, Haoxiang Wang, Ziyan Jiang, Alexandros Papangelis, Han Zhao
2024 A conf
Towards Practical Non-Adversarial Distribution Matching.
AISTATS
Ziyu Gong, Ben Usman, Han Zhao, David I. Inouye
2024 J jnl
Towards Understanding the Fragility of Multilingual LLMs against Fine-Tuning Attacks.
CoRR
Samuele Poppi, Zheng-Xin Yong, Yifei He, Bobbie Chern, Han Zhao, Aobo Yang, Jianfeng Chi
2024 J jnl
Towards Understanding the Role of Sharpness-Aware Minimization Algorithms for Out-of-Distribution Generalization.
CoRR
Samuel Schapiro, Han Zhao
2024 J jnl
Transforming the Hybrid Cloud for Emerging AI Workloads.
CoRR
Deming Chen, Alaa Youssef, Ruchi Pendse, André Schleife, Bryan K. Clark, Hendrik F. Hamann, Jingrui He, Teodoro Laino, Lav R. Varshney, Yuxiong Wang, Avirup Sil, Reyhaneh Jabbarvand, Tianyin Xu, Volodymyr V. Kindratenko, Carlos H. A. Costa, Sarita V. Adve, Charith Mendis, Minjia Zhang, Santiago Núñez-Corrales, Raghu K. Ganti, Mudhakar Srivatsa, Nam Sung Kim, Josep Torrellas, Jian Huang, Seetharami R. Seelam, Klara Nahrstedt, Tarek F. Abdelzaher, Tamar Eilam, Huimin Zhao, Matteo Manica, Ravishankar K. Iyer, Martin Hirzel, Vikram S. Adve, Darko Marinov, Hubertus Franke, Hanghang Tong, Elizabeth A. Ainsworth, Han Zhao, Deepak Vasisht, Minh Do, Fábio Oliveira, Giovanni Pacifici, Ruchir Puri, Priya Nagpurkar
2023 J jnl
Adaptation Augmented Model-based Policy Optimization.
J. Mach. Learn. Res.
Jian Shen, Hang Lai, Minghuan Liu, Han Zhao, Yong Yu, Weinan Zhang
2023 B conf
Adaptive Power Method: Eigenvector Estimation from Sampled Data.
ALT
Seiyun Shin, Han Zhao, Ilan Shomorony
2023 J jnl
An Empirical Study of Simplicial Representation Learning with Wasserstein Distance.
CoRR
Makoto Yamada, Yuki Takezawa, Guillaume Houry, Kira Michaela Dusterwald, Déborah Sulem, Han Zhao, Yao-Hung Hubert Tsai
2023 J jnl
Costs and Benefits of Fair Regression.
Trans. Mach. Learn. Res.
Han Zhao
2023 A* conf
Efficient Learning of Linear Graph Neural Networks via Node Subsampling.
NeurIPS
Seiyun Shin, Ilan Shomorony, Han Zhao
2023 J jnl
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods.
CoRR
Xiaotian Han, Jianfeng Chi, Yu Chen, Qifan Wang, Han Zhao, Na Zou, Xia Hu
2023 A* conf
Fair and Optimal Classification via Post-Processing.
ICML
Ruicheng Xian, Lang Yin, Han Zhao
2023 A conf
FedMM: A Communication Efficient Solver for Federated Adversarial Domain Adaptation.
AAMAS
Yan Shen, Jian Du, Han Zhao, Zhanghexuan Ji, Chunwei Ma, Mingchen Gao
2023 J jnl
Gradual Domain Adaptation: Theory and Algorithms.
CoRR
Yifei He, Haoxiang Wang, Bo Li, Han Zhao
2023 J jnl
In-Context Learning of Large Language Models Explained as Kernel Regression.
CoRR
Chi Han, Ziqi Wang, Han Zhao, Heng Ji
2023 J jnl
Invariant-Feature Subspace Recovery: A New Class of Provable Domain Generalization Algorithms.
CoRR
Haoxiang Wang, Gargi Balasubramaniam, Haozhe Si, Bo Li, Han Zhao
2023 A* conf
Learning List-Level Domain-Invariant Representations for Ranking.
NeurIPS
Ruicheng Xian, Honglei Zhuang, Zhen Qin, Hamed Zamani, Jing Lu, Ji Ma, Kai Hui, Han Zhao, Xuanhui Wang, Michael Bendersky
2023 J jnl
Learning Multiplex Embeddings on Text-rich Networks with One Text Encoder.
CoRR
Bowen Jin, Wentao Zhang, Yu Zhang, Yu Meng, Han Zhao, Jiawei Han
2023 A* conf
Learning Structured Representations by Embedding Class Hierarchy.
ICLR
Siqi Zeng, Remi Tachet des Combes, Han Zhao
2023 J jnl
Mitigating the Alignment Tax of RLHF.
CoRR
Yong Lin, Hangyu Lin, Wei Xiong, Shizhe Diao, Jianmeng Liu, Jipeng Zhang, Rui Pan, Haoxiang Wang, Wenbin Hu, Hanning Zhang, Hanze Dong, Renjie Pi, Han Zhao, Nan Jiang, Yuan Yao, Tong Zhang
2023 A* conf
Revisiting Scalarization in Multi-Task Learning: A Theoretical Perspective.
NeurIPS
Yuzheng Hu, Ruicheng Xian, Qilong Wu, Qiuling Fan, Lang Yin, Han Zhao
2023 J jnl
Revisiting Scalarization in Multi-Task Learning: A Theoretical Perspective.
CoRR
Yuzheng Hu, Ruicheng Xian, Qilong Wu, Qiuling Fan, Lang Yin, Han Zhao
2023 — conf
SC
ICCV (Workshops)
Zikun Chen, Han Zhao, Parham Aarabi, Ruowei Jiang
2023 J jnl
SC2GAN: Rethinking Entanglement by Self-correcting Correlated GAN Space.
CoRR
Zikun Chen, Han Zhao, Parham Aarabi, Ruowei Jiang
2023 A* conf
Structural Re-weighting Improves Graph Domain Adaptation.
ICML
Shikun Liu, Tianchun Li, Yongbin Feng, Nhan Tran, Han Zhao, Qiang Qiu, Pan Li
2023 J jnl
Structural Re-weighting Improves Graph Domain Adaptation.
CoRR
Shikun Liu, Tianchun Li, Yongbin Feng, Nhan Tran, Han Zhao, Qiang Qiu, Pan Li
2023 J jnl
Towards Practical Non-Adversarial Distribution Alignment via Variational Bounds.
CoRR
Ziyu Gong, Ben Usman, Han Zhao, David I. Inouye
2023 — conf
Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphs.
ECML/PKDD (3)
Costas Mavromatis, Vassilis N. Ioannidis, Shen Wang, Da Zheng, Soji Adeshina, Jun Ma, Han Zhao, Christos Faloutsos, George Karypis
2023 J jnl
Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphs.
CoRR
Costas Mavromatis, Vassilis N. Ioannidis, Shen Wang, Da Zheng, Soji Adeshina, Jun Ma, Han Zhao, Christos Faloutsos, George Karypis
2023 A* conf
Understanding and Constructing Latent Modality Structures in Multi-Modal Representation Learning.
CVPR
Qian Jiang, Changyou Chen, Han Zhao, Liqun Chen, Qing Ping, Son Dinh Tran, Yi Xu, Belinda Zeng, Trishul Chilimbi
2023 J jnl
Understanding and Constructing Latent Modality Structures in Multi-modal Representation Learning.
CoRR
Qian Jiang, Changyou Chen, Han Zhao, Liqun Chen, Qing Ping, Son Dinh Tran, Yi Xu, Belinda Zeng, Trishul Chilimbi
2023 A* conf
Understanding the Impact of Adversarial Robustness on Accuracy Disparity.
ICML
Yuzheng Hu, Fan Wu, Hongyang Zhang, Han Zhao
2022 J jnl
A Review of Single-Source Deep Unsupervised Visual Domain Adaptation.
IEEE Trans. Neural Networks Learn. Syst.
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
2022 J jnl
Algorithms and Theory for Supervised Gradual Domain Adaptation.
CoRR
Jing Dong, Shiji Zhou, Baoxiang Wang, Han Zhao
2022 J jnl
Algorithms and Theory for Supervised Gradual Domain Adaptation.
Trans. Mach. Learn. Res.
Jing Dong, Shiji Zhou, Baoxiang Wang, Han Zhao
2022 A* conf
Conditional Contrastive Learning with Kernel.
ICLR
Yao-Hung Hubert Tsai, Tianqin Li, Martin Q. Ma, Han Zhao, Kun Zhang, Louis-Philippe Morency, Ruslan Salakhutdinov
2022 J jnl
Conditional Contrastive Learning with Kernel.
CoRR
Yao-Hung Hubert Tsai, Tianqin Li, Martin Q. Ma, Han Zhao, Kun Zhang, Louis-Philippe Morency, Ruslan Salakhutdinov
2022 — conf
Conditional Supervised Contrastive Learning for Fair Text Classification.
EMNLP (Findings)
Jianfeng Chi, William Shand, Yaodong Yu, Kai-Wei Chang, Han Zhao, Yuan Tian
2022 J jnl
Conditional Supervised Contrastive Learning for Fair Text Classification.
CoRR
Jianfeng Chi, William Shand, Yaodong Yu, Kai-Wei Chang, Han Zhao, Yuan Tian
2022 A* conf
Cross-Lingual Transfer with Class-Weighted Language-Invariant Representations.
ICLR
Ruicheng Xian, Heng Ji, Han Zhao
2022 — conf
Exploring Gradient-Based Multi-directional Controls in GANs.
ECCV (23)
Zikun Chen, Ruowei Jiang, Brendan Duke, Han Zhao, Parham Aarabi
2022 J jnl
Exploring Gradient-based Multi-directional Controls in GANs.
CoRR
Zikun Chen, Ruowei Jiang, Brendan Duke, Han Zhao, Parham Aarabi
2022 J jnl
FOCUS: Fairness via Agent-Awareness for Federated Learning on Heterogeneous Data.
CoRR
Wenda Chu, Chulin Xie, Boxin Wang, Linyi Li, Lang Yin, Han Zhao, Bo Li
2022 J jnl
Fair and Optimal Classification via Transports to Wasserstein-Barycenter.
CoRR
Ruicheng Xian, Lang Yin, Han Zhao
2022 J jnl
Fundamental Limits and Tradeoffs in Invariant Representation Learning.
J. Mach. Learn. Res.
Han Zhao, Chen Dan, Bryon Aragam, Tommi S. Jaakkola, Geoffrey J. Gordon, Pradeep Ravikumar
2022 J jnl
Greedy Modality Selection via Approximate Submodular Maximization.
CoRR
Runxiang Cheng, Gargi Balasubramaniam, Yifei He, Yao-Hung Hubert Tsai, Han Zhao
2022 A conf
Greedy modality selection via approximate submodular maximization.
UAI
Runxiang Cheng, Gargi Balasubramaniam, Yifei He, Yao-Hung Hubert Tsai, Han Zhao
2022 J jnl
Inherent Tradeoffs in Learning Fair Representations.
J. Mach. Learn. Res.
Han Zhao, Geoffrey J. Gordon
2022 A* conf
Invariant Information Bottleneck for Domain Generalization.
AAAI
Bo Li, Yifei Shen, Yezhen Wang, Wenzhen Zhu, Colorado Reed, Dongsheng Li, Kurt Keutzer, Han Zhao
2022 J jnl
Learning List-Level Domain-Invariant Representations for Ranking.
CoRR
Ruicheng Xian, Honglei Zhuang, Zhen Qin, Hamed Zamani, Jing Lu, Ji Ma, Kai Hui, Han Zhao, Xuanhui Wang, Michael Bendersky
2022 J jnl
Model-Agnostic Multitask Fine-tuning for Few-shot Vision-Language Transfer Learning.
CoRR
Zhenhailong Wang, Hang Yu, Manling Li, Han Zhao, Heng Ji
2022 A conf
Online Continual Adaptation with Active Self-Training.
AISTATS
Shiji Zhou, Han Zhao, Shanghang Zhang, Lianzhe Wang, Heng Chang, Zhi Wang, Wenwu Zhu
2022 A* conf
Provable Domain Generalization via Invariant-Feature Subspace Recovery.
ICML
Haoxiang Wang, Haozhe Si, Bo Li, Han Zhao
2022 J jnl
Provable Domain Generalization via Invariant-Feature Subspace Recovery.
CoRR
Haoxiang Wang, Haozhe Si, Bo Li, Han Zhao
2022 A* conf
Rethinking Controllable Variational Autoencoders.
CVPR
Huajie Shao, Yifei Yang, Haohong Lin, Longzhong Lin, Yizhuo Chen, Qinmin Yang, Han Zhao
2022 A conf
Towards Return Parity in Markov Decision Processes.
AISTATS
Jianfeng Chi, Jian Shen, Xinyi Dai, Weinan Zhang, Yuan Tian, Han Zhao
2022 A* conf
Understanding Gradual Domain Adaptation: Improved Analysis, Optimal Path and Beyond.
ICML
Haoxiang Wang, Bo Li, Han Zhao
2022 J jnl
Understanding Gradual Domain Adaptation: Improved Analysis, Optimal Path and Beyond.
CoRR
Haoxiang Wang, Bo Li, Han Zhao
2022 J jnl
Understanding the Impact of Adversarial Robustness on Accuracy Disparity.
CoRR
Yuzheng Hu, Fan Wu, Hongyang Zhang, Han Zhao
2021 A* conf
Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation.
ICML
Haoxiang Wang, Han Zhao, Bo Li
2021 J jnl
Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation.
CoRR
Haoxiang Wang, Han Zhao, Bo Li
2021 J jnl
Conditional Contrastive Learning: Removing Undesirable Information in Self-Supervised Representations.
CoRR
Yao-Hung Hubert Tsai, Martin Q. Ma, Han Zhao, Kun Zhang, Louis-Philippe Morency, Ruslan Salakhutdinov
2021 J jnl
Costs and Benefits of Wasserstein Fair Regression.
CoRR
Han Zhao
2021 — conf
EventKE: Event-Enhanced Knowledge Graph Embedding.
EMNLP (Findings)
Zixuan Zhang, Hongwei Wang, Han Zhao, Hanghang Tong, Heng Ji
2021 A* conf
Information Obfuscation of Graph Neural Networks.
ICML
Peiyuan Liao, Han Zhao, Keyulu Xu, Tommi S. Jaakkola, Geoffrey J. Gordon, Stefanie Jegelka, Ruslan Salakhutdinov
2021 J jnl
Invariant Information Bottleneck for Domain Generalization.
CoRR
Bo Li, Yifei Shen, Yezhen Wang, Wenzhen Zhu, Colorado J. Reed, Jun Zhang, Dongsheng Li, Kurt Keutzer, Han Zhao
2021 A* conf
Learning Invariant Representations and Risks for Semi-Supervised Domain Adaptation.
CVPR
Bo Li, Yezhen Wang, Shanghang Zhang, Dongsheng Li, Kurt Keutzer, Trevor Darrell, Han Zhao
2021 A* conf
Machine Learning for Consumers and Markets.
KDD
Wen Wang, Han Zhao, Dokyun Lee, George H. Chen
2021 A* conf
On Dyadic Fairness: Exploring and Mitigating Bias in Graph Connections.
ICLR
Peizhao Li, Yifei Wang, Han Zhao, Pengyu Hong, Hongfu Liu
2021 J jnl
Online Continual Adaptation with Active Self-Training.
CoRR
Shiji Zhou, Han Zhao, Shanghang Zhang, Lianzhe Wang, Heng Chang, Zhi Wang, Wenwu Zhu
2021 A* conf
Quantifying and Improving Transferability in Domain Generalization.
NeurIPS
Guojun Zhang, Han Zhao, Yaoliang Yu, Pascal Poupart
2021 J jnl
Quantifying and Improving Transferability in Domain Generalization.
CoRR
Guojun Zhang, Han Zhao, Yaoliang Yu, Pascal Poupart
2021 A* conf
Self-supervised Representation Learning with Relative Predictive Coding.
ICLR
Yao-Hung Hubert Tsai, Martin Q. Ma, Muqiao Yang, Han Zhao, Louis-Philippe Morency, Ruslan Salakhutdinov
2021 J jnl
Self-supervised Representation Learning with Relative Predictive Coding.
CoRR
Yao-Hung Hubert Tsai, Martin Q. Ma, Muqiao Yang, Han Zhao, Louis-Philippe Morency, Ruslan Salakhutdinov
2021 J jnl
Towards Return Parity in Markov Decision Processes.
CoRR
Jianfeng Chi, Jian Shen, Xinyi Dai, Weinan Zhang, Yuan Tian, Han Zhao
2021 — —
Towards a Unified Framework for Learning and Reasoning.
Han Zhao
2021 A* conf
Understanding and Mitigating Accuracy Disparity in Regression.
ICML
Jianfeng Chi, Yuan Tian, Geoffrey J. Gordon, Han Zhao
2021 J jnl
Understanding and Mitigating Accuracy Disparity in Regression.
CoRR
Jianfeng Chi, Yuan Tian, Geoffrey J. Gordon, Han Zhao
2020 J jnl
A Review of Single-Source Deep Unsupervised Visual Domain Adaptation.
CoRR
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
2020 A* conf
Conditional Learning of Fair Representations.
ICLR
Han Zhao, Amanda Coston, Tameem Adel, Geoffrey J. Gordon
2020 A* conf
Continual Learning with Adaptive Weights (CLAW).
ICLR
Tameem Adel, Han Zhao, Richard E. Turner
2020 A* conf
Deep Fair Clustering for Visual Learning.
CVPR
Peizhao Li, Han Zhao, Hongfu Liu
2020 A* conf
Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift.
NeurIPS
Remi Tachet des Combes, Han Zhao, Yu-Xiang Wang, Geoffrey J. Gordon
2020 J jnl
Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift.
CoRR
Remi Tachet des Combes, Han Zhao, Yu-Xiang Wang, Geoffrey J. Gordon
2020 A* conf
DyCRS: Dynamic Interpretable Postoperative Complication Risk Scoring.
WWW
Wen Wang, Han Zhao, Honglei Zhuang, Nirav Shah, Rema Padman
2020 J jnl
Fundamental Limits and Tradeoffs in Invariant Representation Learning.
CoRR
Han Zhao, Chen Dan, Bryon Aragam, Tommi S. Jaakkola, Geoffrey J. Gordon, Pradeep Ravikumar
2020 J jnl
Graph Adversarial Networks: Protecting Information against Adversarial Attacks.
CoRR
Peiyuan Liao, Han Zhao, Keyulu Xu, Tommi S. Jaakkola, Geoffrey J. Gordon, Stefanie Jegelka, Ruslan Salakhutdinov
2020 J jnl
Learning Invariant Representations and Risks for Semi-supervised Domain Adaptation.
CoRR
Bo Li, Yezhen Wang, Shanghang Zhang, Dongsheng Li, Trevor Darrell, Kurt Keutzer, Han Zhao
2020 A* conf
Model-based Policy Optimization with Unsupervised Model Adaptation.
NeurIPS
Jian Shen, Han Zhao, Weinan Zhang, Yong Yu
2020 J jnl
Model-based Policy Optimization with Unsupervised Model Adaptation.
CoRR
Jian Shen, Han Zhao, Weinan Zhang, Yong Yu
2020 A* conf
Neural Methods for Point-wise Dependency Estimation.
NeurIPS
Yao-Hung Hubert Tsai, Han Zhao, Makoto Yamada, Louis-Philippe Morency, Ruslan Salakhutdinov
2020 J jnl
Neural Methods for Point-wise Dependency Estimation.
CoRR
Yao-Hung Hubert Tsai, Han Zhao, Makoto Yamada, Louis-Philippe Morency, Ruslan Salakhutdinov
2020 A* conf
On Learning Language-Invariant Representations for Universal Machine Translation.
ICML
Han Zhao, Junjie Hu, Andrej Risteski
2020 J jnl
On Learning Language-Invariant Representations for Universal Machine Translation.
CoRR
Han Zhao, Junjie Hu, Andrej Risteski
2020 A* conf
Trade-offs and Guarantees of Adversarial Representation Learning for Information Obfuscation.
NeurIPS
Han Zhao, Jianfeng Chi, Yuan Tian, Geoffrey J. Gordon
2019 B conf
Active Learning of Strict Partial Orders: A Case Study on Concept Prerequisite Relations.
EDM
Chen Liang, Jianbo Ye, Han Zhao, Bart Pursel, C. Lee Giles
2019 J jnl
Adversarial Task-Specific Privacy Preservation under Attribute Attack.
CoRR
Han Zhao, Jianfeng Chi, Yuan Tian, Geoffrey J. Gordon
2019 J jnl
Conditional Learning of Fair Representations.
CoRR
Han Zhao, Amanda Coston, Tameem Adel, Geoffrey J. Gordon
2019 J jnl
Continual Learning with Adaptive Weights (CLAW).
CoRR
Tameem Adel, Han Zhao, Richard E. Turner
2019 A conf
Deep Generative and Discriminative Domain Adaptation.
AAMAS
Han Zhao, Junjie Hu, Zhenyao Zhu, Adam Coates, Geoffrey J. Gordon
2019 A conf
Efficient Multitask Feature and Relationship Learning.
UAI
Han Zhao, Otilia Stretcu, Alexander J. Smola, Geoffrey J. Gordon
2019 J jnl
Inherent Tradeoffs in Learning Fair Representation.
CoRR
Han Zhao, Geoffrey J. Gordon
2019 A* conf
Inherent Tradeoffs in Learning Fair Representations.
NeurIPS
Han Zhao, Geoffrey J. Gordon
2019 A* conf
Learning Neural Networks with Adaptive Regularization.
NeurIPS
Han Zhao, Yao-Hung Hubert Tsai, Ruslan Salakhutdinov, Geoffrey J. Gordon
2019 J jnl
Learning Neural Networks with Adaptive Regularization.
CoRR
Han Zhao, Yao-Hung Hubert Tsai, Ruslan Salakhutdinov, Geoffrey J. Gordon
2019 J jnl
On Learning Invariant Representation for Domain Adaptation.
CoRR
Han Zhao, Remi Tachet des Combes, Kun Zhang, Geoffrey J. Gordon
2019 A* conf
On Learning Invariant Representations for Domain Adaptation.
ICML
Han Zhao, Remi Tachet des Combes, Kun Zhang, Geoffrey J. Gordon
2019 A* conf
On Strategyproof Conference Peer Review.
IJCAI
Yichong Xu, Han Zhao, Xiaofei Shi, Nihar B. Shah
2018 J jnl
Active Learning of Strict Partial Orders: A Case Study on Concept Prerequisite Relations.
CoRR
Chen Liang, Jianbo Ye, Han Zhao, Bart Pursel, C. Lee Giles
2018 A* conf
Adversarial Multiple Source Domain Adaptation.
NeurIPS
Han Zhao, Shanghang Zhang, Guanhang Wu, José M. F. Moura, João Paulo Costeira, Geoffrey J. Gordon
2018 Misc conf
Convolutional-Recurrent Neural Networks for Speech Enhancement.
ICASSP
Han Zhao, Shuayb Zarar, Ivan Tashev, Chin-Hui Lee
2018 J jnl
Convolutional-Recurrent Neural Networks for Speech Enhancement.
CoRR
Han Zhao, Shuayb Zarar, Ivan Tashev, Chin-Hui Lee
2018 A conf
Frank-Wolfe Optimization for Symmetric-NMF under Simplicial Constraint.
UAI
Han Zhao, Geoffrey J. Gordon
2018 — conf
Multiple Source Domain Adaptation with Adversarial Learning.
ICLR (Workshop)
Han Zhao, Shanghang Zhang, Guanhang Wu, João Paulo Costeira, José M. F. Moura, Geoffrey J. Gordon
2018 J jnl
On Strategyproof Conference Peer Review.
CoRR
Yichong Xu, Han Zhao, Xiaofei Shi, Nihar B. Shah
2017 J jnl
Discovering Order in Unordered Datasets: Generative Markov Networks.
CoRR
Yao-Hung Hubert Tsai, Han Zhao, Ruslan Salakhutdinov, Nebojsa Jojic
2017 J jnl
Efficient Computation of Moments in Sum-Product Networks.
CoRR
Han Zhao, Geoffrey J. Gordon
2017 J jnl
Efficient Multi-task Feature and Relationship Learning.
CoRR
Han Zhao, Otilia Stretcu, Renato Negrinho, Alexander J. Smola, Geoffrey J. Gordon
2017 J jnl
Frank-Wolfe Optimization for Symmetric-NMF under Simplicial Constraint.
CoRR
Han Zhao, Geoffrey J. Gordon
2017 — conf
Linear Time Computation of Moments in Sum-Product Networks.
NIPS
Han Zhao, Geoffrey J. Gordon
2017 J jnl
Multiple Source Domain Adaptation with Adversarial Training of Neural Networks.
CoRR
Han Zhao, Shanghang Zhang, Guanhang Wu, João Paulo Costeira, José M. F. Moura, Geoffrey J. Gordon
2017 J jnl
Principled Hybrids of Generative and Discriminative Domain Adaptation.
CoRR
Han Zhao, Zhenyao Zhu, Junjie Hu, Adam Coates, Geoffrey J. Gordon
2017 A* conf
Unsupervised Domain Adaptation with a Relaxed Covariate Shift Assumption.
AAAI
Tameem Adel, Han Zhao, Alexander Wong
2016 — conf
A Unified Approach for Learning the Parameters of Sum-Product Networks.
NIPS
Han Zhao, Pascal Poupart, Geoffrey J. Gordon
2016 J jnl
A Unified Approach for Learning the Parameters of Sum-Product Networks.
CoRR
Han Zhao, Pascal Poupart, Geoffrey J. Gordon
2016 A* conf
Collapsed Variational Inference for Sum-Product Networks.
ICML
Han Zhao, Tameem Adel, Geoffrey J. Gordon, Brandon Amos
2016 — conf
Online Algorithms for Sum-Product Networks with Continuous Variables.
Probabilistic Graphical Models
Priyank Jaini, Abdullah Rashwan, Han Zhao, Yue Liu, Ershad Banijamali, Zhitang Chen, Pascal Poupart
2016 A conf
Online and Distributed Bayesian Moment Matching for Parameter Learning in Sum-Product Networks.
AISTATS
Abdullah Rashwan, Han Zhao, Pascal Poupart
2015 J jnl
Global Network Alignment in the Context of Aging.
IEEE ACM Trans. Comput. Biol. Bioinform.
Fazle Elahi Faisal, Han Zhao, Tijana Milenkovic
2015 A* conf
On the Relationship between Sum-Product Networks and Bayesian Networks.
ICML
Han Zhao, Mazen Melibari, Pascal Poupart
2015 J jnl
On the Relationship between Sum-Product Networks and Bayesian Networks.
CoRR
Han Zhao, Mazen Melibari, Pascal Poupart
2015 A* conf
Self-Adaptive Hierarchical Sentence Model.
IJCAI
Han Zhao, Zhengdong Lu, Pascal Poupart
2015 J jnl
Self-Adaptive Hierarchical Sentence Model.
CoRR
Han Zhao, Zhengdong Lu, Pascal Poupart
2015 A* conf
SoF: Soft-Cluster Matrix Factorization for Probabilistic Clustering.
AAAI
Han Zhao, Pascal Poupart, Yongfeng Zhang, Martin Lysy
2014 J jnl
A Sober Look at Spectral Learning.
CoRR
Han Zhao, Pascal Poupart
2014 — conf
Global network alignment in the context of aging.
BCB
Fazle Elahi Faisal, Han Zhao, Tijana Milenkovic
2013 — conf
Global Network Alignment In The Context Of Aging.
BCB
Tijana Milenkovic, Han Zhao, Fazle Elahi Faisal
2013 — conf
Using Global Network Alignment In The Context Of Aging.
BCB
Tijana Milenkovic, Han Zhao, Fazle Elahi Faisal