Using Global Network Alignment In The Context Of Aging. - Tijana Milenkovic; Han Zhao 002; Fazle Elahi Faisal (BCB, 2013)

A Sober Look at Spectral Learning. - Han Zhao 002; Pascal Poupart (CoRR, 2014)

SoF: Soft-Cluster Matrix Factorization for Probabilistic Clustering. - Han Zhao 002; Pascal Poupart; Yongfeng Zhang; Martin Lysy (AAAI, 2015)

On the Relationship between Sum-Product Networks and Bayesian Networks. - Han Zhao 002; Mazen Melibari; Pascal Poupart (ICML, 2015)

Self-Adaptive Hierarchical Sentence Model. - Han Zhao 002; Zhengdong Lu; Pascal Poupart (IJCAI, 2015)

Global Network Alignment in the Context of Aging. - Fazle Elahi Faisal; Han Zhao 002; Tijana Milenkovic (IEEE ACM Trans. Comput. Biol. Bioinform., 2015)

Online and Distributed Bayesian Moment Matching for Parameter Learning in Sum-Product Networks. - Abdullah Rashwan; Han Zhao 002; Pascal Poupart (AISTATS, 2016)

Collapsed Variational Inference for Sum-Product Networks. - Han Zhao 002; Tameem Adel; Geoffrey J. Gordon; Brandon Amos (ICML, 2016)

A Unified Approach for Learning the Parameters of Sum-Product Networks. - Han Zhao 002; Pascal Poupart; Geoffrey J. Gordon (NIPS, 2016)

Online Algorithms for Sum-Product Networks with Continuous Variables. - Priyank Jaini; Abdullah Rashwan; Han Zhao 002; Yue Liu; Ershad Banijamali; Zhitang Chen; Pascal Poupart (Probabilistic Graphical Models, 2016)

Unsupervised Domain Adaptation with a Relaxed Covariate Shift Assumption. - Tameem Adel; Han Zhao 002; Alexander Wong (AAAI, 2017)

Linear Time Computation of Moments in Sum-Product Networks. - Han Zhao 002; Geoffrey J. Gordon (NIPS, 2017)

Efficient Computation of Moments in Sum-Product Networks. - Han Zhao 002; Geoffrey J. Gordon (CoRR, 2017)

Efficient Multi-task Feature and Relationship Learning. - Han Zhao 002; Otilia Stretcu; Renato Negrinho; Alexander J. Smola; Geoffrey J. Gordon (CoRR, 2017)

Principled Hybrids of Generative and Discriminative Domain Adaptation. - Han Zhao 002; Zhenyao Zhu; Junjie Hu 001; Adam Coates 002; Geoffrey J. Gordon (CoRR, 2017)

Multiple Source Domain Adaptation with Adversarial Training of Neural Networks. - Han Zhao 002; Shanghang Zhang; Guanhang Wu; João Paulo Costeira; José M. F. Moura; Geoffrey J. Gordon (CoRR, 2017)

Discovering Order in Unordered Datasets: Generative Markov Networks. - Yao-Hung Hubert Tsai; Han Zhao 002; Ruslan Salakhutdinov; Nebojsa Jojic (CoRR, 2017)

Convolutional-Recurrent Neural Networks for Speech Enhancement. - Han Zhao 002; Shuayb Zarar; Ivan Tashev; Chin-Hui Lee (ICASSP, 2018)

Multiple Source Domain Adaptation with Adversarial Learning. - Han Zhao 002; Shanghang Zhang; Guanhang Wu; João Paulo Costeira; José M. F. Moura; Geoffrey J. Gordon (ICLR (Workshop), 2018)

Adversarial Multiple Source Domain Adaptation. - Han Zhao 002; Shanghang Zhang; Guanhang Wu; José M. F. Moura; João Paulo Costeira; Geoffrey J. Gordon (NeurIPS, 2018)

Frank-Wolfe Optimization for Symmetric-NMF under Simplicial Constraint. - Han Zhao 002; Geoffrey J. Gordon (UAI, 2018)

Deep Generative and Discriminative Domain Adaptation. - Han Zhao 002; Junjie Hu 001; Zhenyao Zhu; Adam Coates 002; Geoffrey J. Gordon (AAMAS, 2019)

Active Learning of Strict Partial Orders: A Case Study on Concept Prerequisite Relations. - Chen Liang 001; Jianbo Ye; Han Zhao 002; Bart Pursel; C. Lee Giles (EDM, 2019)

On Learning Invariant Representations for Domain Adaptation. - Han Zhao 002; Remi Tachet des Combes; Kun Zhang 001; Geoffrey J. Gordon (ICML, 2019)

On Strategyproof Conference Peer Review. - Yichong Xu; Han Zhao 002; Xiaofei Shi; Nihar B. Shah (IJCAI, 2019)

Learning Neural Networks with Adaptive Regularization. - Han Zhao 002; Yao-Hung Hubert Tsai; Ruslan Salakhutdinov; Geoffrey J. Gordon (NeurIPS, 2019)

Efficient Multitask Feature and Relationship Learning. - Han Zhao 002; Otilia Stretcu; Alexander J. Smola; Geoffrey J. Gordon (UAI, 2019)

On Learning Invariant Representation for Domain Adaptation. - Han Zhao 002; Remi Tachet des Combes; Kun Zhang 001; Geoffrey J. Gordon (CoRR, 2019)

Adversarial Task-Specific Privacy Preservation under Attribute Attack. - Han Zhao 002; Jianfeng Chi; Yuan Tian 001; Geoffrey J. Gordon (CoRR, 2019)

Inherent Tradeoffs in Learning Fair Representation. - Han Zhao 002; Geoffrey J. Gordon (CoRR, 2019)

Deep Fair Clustering for Visual Learning. - Peizhao Li; Han Zhao 002; Hongfu Liu 001 (CVPR, 2020)

Conditional Learning of Fair Representations. - Han Zhao 002; Amanda Coston; Tameem Adel; Geoffrey J. Gordon (ICLR, 2020)

Continual Learning with Adaptive Weights (CLAW). - Tameem Adel; Han Zhao 002; Richard E. Turner (ICLR, 2020)

On Learning Language-Invariant Representations for Universal Machine Translation. - Han Zhao 002; Junjie Hu 001; Andrej Risteski (ICML, 2020)

Trade-offs and Guarantees of Adversarial Representation Learning for Information Obfuscation. - Han Zhao 002; Jianfeng Chi; Yuan Tian 001; Geoffrey J. Gordon (NeurIPS, 2020)

Model-based Policy Optimization with Unsupervised Model Adaptation. - Jian Shen 003; Han Zhao 002; Weinan Zhang 001; Yong Yu 001 (NeurIPS, 2020)

Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift. - Remi Tachet des Combes; Han Zhao 002; Yu-Xiang Wang 003; Geoffrey J. Gordon (NeurIPS, 2020)

Neural Methods for Point-wise Dependency Estimation. - Yao-Hung Hubert Tsai; Han Zhao 002; Makoto Yamada; Louis-Philippe Morency; Ruslan Salakhutdinov (NeurIPS, 2020)

DyCRS: Dynamic Interpretable Postoperative Complication Risk Scoring. - Wen Wang; Han Zhao 002; Honglei Zhuang; Nirav Shah 004; Rema Padman (WWW, 2020)

Graph Adversarial Networks: Protecting Information against Adversarial Attacks. - Peiyuan Liao; Han Zhao 002; Keyulu Xu; Tommi S. Jaakkola; Geoffrey J. Gordon; Stefanie Jegelka; Ruslan Salakhutdinov (CoRR, 2020)

Learning Invariant Representations and Risks for Semi-Supervised Domain Adaptation. - Bo Li 080; Yezhen Wang; Shanghang Zhang; Dongsheng Li 002; Kurt Keutzer; Trevor Darrell; Han Zhao 002 (CVPR, 2021)

EventKE: Event-Enhanced Knowledge Graph Embedding. - Zixuan Zhang; Hongwei Wang; Han Zhao 002; Hanghang Tong; Heng Ji 001 (EMNLP (Findings), 2021)

On Dyadic Fairness: Exploring and Mitigating Bias in Graph Connections. - Peizhao Li; Yifei Wang 002; Han Zhao 002; Pengyu Hong; Hongfu Liu 001 (ICLR, 2021)

Self-supervised Representation Learning with Relative Predictive Coding. - Yao-Hung Hubert Tsai; Martin Q. Ma; Muqiao Yang; Han Zhao 002; Louis-Philippe Morency; Ruslan Salakhutdinov (ICLR, 2021)

Understanding and Mitigating Accuracy Disparity in Regression. - Jianfeng Chi; Yuan Tian 001; Geoffrey J. Gordon; Han Zhao 002 (ICML, 2021)

Information Obfuscation of Graph Neural Networks. - Peiyuan Liao; Han Zhao 002; Keyulu Xu; Tommi S. Jaakkola; Geoffrey J. Gordon; Stefanie Jegelka; Ruslan Salakhutdinov (ICML, 2021)

Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation. - Haoxiang Wang 003; Han Zhao 002; Bo Li 026 (ICML, 2021)

Machine Learning for Consumers and Markets. - Wen Wang; Han Zhao 002; Dokyun Lee; George H. Chen (KDD, 2021)

Quantifying and Improving Transferability in Domain Generalization. - Guojun Zhang; Han Zhao 002; Yaoliang Yu; Pascal Poupart (NeurIPS, 2021)

Conditional Contrastive Learning: Removing Undesirable Information in Self-Supervised Representations. - Yao-Hung Hubert Tsai; Martin Q. Ma; Han Zhao 002; Kun Zhang 001; Louis-Philippe Morency; Ruslan Salakhutdinov (CoRR, 2021)

Invariant Information Bottleneck for Domain Generalization. - Bo Li 080; Yifei Shen; Yezhen Wang; Wenzhen Zhu; Colorado J. Reed; Jun Zhang 004; Dongsheng Li 002; Kurt Keutzer; Han Zhao 002 (CoRR, 2021)

Costs and Benefits of Wasserstein Fair Regression. - Han Zhao 002 (CoRR, 2021)

Towards a Unified Framework for Learning and Reasoning. - Han Zhao 002 (2021)

Invariant Information Bottleneck for Domain Generalization. - Bo Li 080; Yifei Shen; Yezhen Wang; Wenzhen Zhu; Colorado Reed; Dongsheng Li 002; Kurt Keutzer; Han Zhao 002 (AAAI, 2022)

Towards Return Parity in Markov Decision Processes. - Jianfeng Chi; Jian Shen 003; Xinyi Dai; Weinan Zhang 001; Yuan Tian 001; Han Zhao 002 (AISTATS, 2022)

Online Continual Adaptation with Active Self-Training. - Shiji Zhou; Han Zhao 002; Shanghang Zhang; Lianzhe Wang; Heng Chang; Zhi Wang 001; Wenwu Zhu 001 (AISTATS, 2022)

Rethinking Controllable Variational Autoencoders. - Huajie Shao; Yifei Yang; Haohong Lin; Longzhong Lin; Yizhuo Chen; Qinmin Yang; Han Zhao 002 (CVPR, 2022)

Exploring Gradient-Based Multi-directional Controls in GANs. - Zikun Chen; Ruowei Jiang; Brendan Duke; Han Zhao 002; Parham Aarabi (ECCV (23), 2022)

Conditional Supervised Contrastive Learning for Fair Text Classification. - Jianfeng Chi; William Shand; Yaodong Yu; Kai-Wei Chang; Han Zhao 002; Yuan Tian 001 (EMNLP (Findings), 2022)

Conditional Contrastive Learning with Kernel. - Yao-Hung Hubert Tsai; Tianqin Li; Martin Q. Ma; Han Zhao 002; Kun Zhang 001; Louis-Philippe Morency; Ruslan Salakhutdinov (ICLR, 2022)

Cross-Lingual Transfer with Class-Weighted Language-Invariant Representations. - Ruicheng Xian; Heng Ji 001; Han Zhao 002 (ICLR, 2022)

Understanding Gradual Domain Adaptation: Improved Analysis, Optimal Path and Beyond. - Haoxiang Wang 003; Bo Li 026; Han Zhao 002 (ICML, 2022)

Provable Domain Generalization via Invariant-Feature Subspace Recovery. - Haoxiang Wang 003; Haozhe Si; Bo Li 026; Han Zhao 002 (ICML, 2022)

Greedy modality selection via approximate submodular maximization. - Runxiang Cheng; Gargi Balasubramaniam; Yifei He; Yao-Hung Hubert Tsai; Han Zhao 002 (UAI, 2022)

Model-Agnostic Multitask Fine-tuning for Few-shot Vision-Language Transfer Learning. - Zhenhailong Wang; Hang Yu; Manling Li; Han Zhao 002; Heng Ji 001 (CoRR, 2022)

FOCUS: Fairness via Agent-Awareness for Federated Learning on Heterogeneous Data. - Wenda Chu; Chulin Xie; Boxin Wang; Linyi Li 001; Lang Yin; Han Zhao 002; Bo Li 026 (CoRR, 2022)

Fair and Optimal Classification via Transports to Wasserstein-Barycenter. - Ruicheng Xian; Lang Yin; Han Zhao 002 (CoRR, 2022)

Fundamental Limits and Tradeoffs in Invariant Representation Learning. - Han Zhao 002; Chen Dan 001; Bryon Aragam; Tommi S. Jaakkola; Geoffrey J. Gordon; Pradeep Ravikumar (J. Mach. Learn. Res., 2022)

Inherent Tradeoffs in Learning Fair Representations. - Han Zhao 002; Geoffrey J. Gordon (J. Mach. Learn. Res., 2022)

Algorithms and Theory for Supervised Gradual Domain Adaptation. - Jing Dong 008; Shiji Zhou; Baoxiang Wang 001; Han Zhao 002 (Trans. Mach. Learn. Res., 2022)

A Review of Single-Source Deep Unsupervised Visual Domain Adaptation. - Sicheng Zhao; Xiangyu Yue 001; Shanghang Zhang; Bo Li 080; Han Zhao 002; Bichen Wu; Ravi Krishna; Joseph E. Gonzalez; Alberto L. Sangiovanni-Vincentelli; Sanjit A. Seshia; Kurt Keutzer (IEEE Trans. Neural Networks Learn. Syst., 2022)

Adaptive Power Method: Eigenvector Estimation from Sampled Data. - Seiyun Shin; Han Zhao 002; Ilan Shomorony (ALT, 2023)

FedMM: A Communication Efficient Solver for Federated Adversarial Domain Adaptation. - Yan Shen 002; Jian Du; Han Zhao 002; Zhanghexuan Ji; Chunwei Ma; Mingchen Gao (AAMAS, 2023)

Understanding and Constructing Latent Modality Structures in Multi-Modal Representation Learning. - Qian Jiang; Changyou Chen; Han Zhao 002; Liqun Chen 001; Qing Ping; Son Dinh Tran; Yi Xu 011; Belinda Zeng; Trishul Chilimbi (CVPR, 2023)

SC2GAN: Rethinking Entanglement by Self-correcting Correlated GAN Space. - Zikun Chen; Han Zhao 002; Parham Aarabi; Ruowei Jiang (ICCV (Workshops), 2023)

Learning Structured Representations by Embedding Class Hierarchy. - Siqi Zeng 001; Remi Tachet des Combes; Han Zhao 002 (ICLR, 2023)

Understanding the Impact of Adversarial Robustness on Accuracy Disparity. - Yuzheng Hu; Fan Wu; Hongyang Zhang 001; Han Zhao 002 (ICML, 2023)

Structural Re-weighting Improves Graph Domain Adaptation. - Shikun Liu; Tianchun Li; Yongbin Feng; Nhan Tran; Han Zhao 002; Qiang Qiu; Pan Li 005 (ICML, 2023)

Fair and Optimal Classification via Post-Processing. - Ruicheng Xian; Lang Yin; Han Zhao 002 (ICML, 2023)

Revisiting Scalarization in Multi-Task Learning: A Theoretical Perspective. - Yuzheng Hu; Ruicheng Xian; Qilong Wu 002; Qiuling Fan; Lang Yin; Han Zhao 002 (NeurIPS, 2023)

Efficient Learning of Linear Graph Neural Networks via Node Subsampling. - Seiyun Shin; Ilan Shomorony; Han Zhao 002 (NeurIPS, 2023)

Learning List-Level Domain-Invariant Representations for Ranking. - Ruicheng Xian; Honglei Zhuang; Zhen Qin 001; Hamed Zamani; Jing Lu; Ji Ma 004; Kai Hui 001; Han Zhao 002; Xuanhui Wang; Michael Bendersky (NeurIPS, 2023)

Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphs. - Costas Mavromatis; Vassilis N. Ioannidis; Shen Wang 005; Da Zheng; Soji Adeshina; Jun Ma 029; Han Zhao 002; Christos Faloutsos; George Karypis (ECML/PKDD (3), 2023)

In-Context Learning of Large Language Models Explained as Kernel Regression. - Chi Han; Ziqi Wang 003; Han Zhao 002; Heng Ji 001 (CoRR, 2023)

Mitigating the Alignment Tax of RLHF. - Yong Lin; Hangyu Lin; Wei Xiong 015; Shizhe Diao; Jianmeng Liu; Jipeng Zhang; Rui Pan 002; Haoxiang Wang 003; Wenbin Hu 002; Hanning Zhang; Hanze Dong; Renjie Pi; et al. (CoRR, 2023)

SC2GAN: Rethinking Entanglement by Self-correcting Correlated GAN Space. - Zikun Chen; Han Zhao 002; Parham Aarabi; Ruowei Jiang (CoRR, 2023)

Learning Multiplex Embeddings on Text-rich Networks with One Text Encoder. - Bowen Jin; Wentao Zhang; Yu Zhang 044; Yu Meng 001; Han Zhao 002; Jiawei Han 001 (CoRR, 2023)

An Empirical Study of Simplicial Representation Learning with Wasserstein Distance. - Makoto Yamada; Yuki Takezawa; Guillaume Houry; Kira Michaela Dusterwald; Déborah Sulem; Han Zhao 002; Yao-Hung Hubert Tsai (CoRR, 2023)

Gradual Domain Adaptation: Theory and Algorithms. - Yifei He; Haoxiang Wang 003; Bo Li 026; Han Zhao 002 (CoRR, 2023)

Towards Practical Non-Adversarial Distribution Alignment via Variational Bounds. - Ziyu Gong; Ben Usman; Han Zhao 002; David I. Inouye (CoRR, 2023)

Invariant-Feature Subspace Recovery: A New Class of Provable Domain Generalization Algorithms. - Haoxiang Wang 003; Gargi Balasubramaniam; Haozhe Si; Bo Li 026; Han Zhao 002 (CoRR, 2023)

Adaptation Augmented Model-based Policy Optimization. - Jian Shen 003; Hang Lai; Minghuan Liu; Han Zhao 002; Yong Yu 001; Weinan Zhang 001 (J. Mach. Learn. Res., 2023)

Costs and Benefits of Fair Regression. - Han Zhao 002 (Trans. Mach. Learn. Res., 2023)

Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewards. - Haoxiang Wang 003; Yong Lin; Wei Xiong 015; Rui Yang 010; Shizhe Diao; Shuang Qiu; Han Zhao 002; Tong Zhang 001 (ACL (1), 2024)

Towards Practical Non-Adversarial Distribution Matching. - Ziyu Gong; Ben Usman; Han Zhao 002; David I. Inouye (AISTATS, 2024)

Fast 1-Wasserstein distance approximations using greedy strategies. - Guillaume Houry; Han Bao 002; Han Zhao 002; Makoto Yamada (AISTATS, 2024)

Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts. - Haoxiang Wang 003; Wei Xiong 015; Tengyang Xie; Han Zhao 002; Tong Zhang 001 (EMNLP (Findings), 2024)

Semi-Supervised Reward Modeling via Iterative Self-Training. - Yifei He; Haoxiang Wang 003; Ziyan Jiang; Alexandros Papangelis; Han Zhao 002 (EMNLP (Findings), 2024)

Mitigating the Alignment Tax of RLHF. - Yong Lin; Hangyu Lin; Wei Xiong 015; Shizhe Diao; Jianmeng Liu; Jipeng Zhang; Rui Pan 002; Haoxiang Wang 003; Wenbin Hu 002; Hanning Zhang; Hanze Dong; Renjie Pi; et al. (EMNLP, 2024)

FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods. - Xiaotian Han; Jianfeng Chi; Yu Chen 022; Qifan Wang 001; Han Zhao 002; Na Zou 001; Xia Hu 001 (ICLR, 2024)

Robust Multi-Task Learning with Excess Risks. - Yifei He; Shiji Zhou; Guojun Zhang; Hyokun Yun; Yi Xu 011; Belinda Zeng; Trishul Chilimbi; Han Zhao 002 (ICML, 2024)

Pairwise Alignment Improves Graph Domain Adaptation. - Shikun Liu; Deyu Zou; Han Zhao 002; Pan Li 005 (ICML, 2024)

Differentially Private Post-Processing for Fair Regression. - Ruicheng Xian; Qiaobo Li; Gautam Kamath 001; Han Zhao 002 (ICML, 2024)

Most Influential Subset Selection: Challenges, Promises, and Beyond. - Yuzheng Hu; Pingbang Hu; Han Zhao 002; Jiaqi W. Ma (NeurIPS, 2024)

FedGTST: Boosting Global Transferability of Federated Models via Statistics Tuning. - Evelyn Ma; Chao Pan 003; S. Rasoul Etesami 001; Han Zhao 002; Olgica Milenkovic (NeurIPS, 2024)

Learning Structured Representations with Hyperbolic Embeddings. - Aditya Sinha; Siqi Zeng 001; Makoto Yamada; Han Zhao 002 (NeurIPS, 2024)

On the Expressive Power of Tree-Structured Probabilistic Circuits. - Lang Yin; Han Zhao 002 (NeurIPS, 2024)

LibMOON: A Gradient-based MultiObjective OptimizatioN Library in PyTorch. - Xiaoyuan Zhang; Liang Zhao; Yingying Yu; Xi Lin 001; Yifan Chen 004; Han Zhao 002; Qingfu Zhang 001 (NeurIPS, 2024)

Fair and optimal prediction via post-processing. - Han Zhao 002 (AI Mag., 2024)

S4: Self-Supervised Sensing Across the Spectrum. - Jayanth Shenoy; Xingjian Davis Zhang; Shlok Mehrotra; Bill Tao; Rem Yang; Han Zhao 002; Deepak Vasisht (CoRR, 2024)

Optimal Group Fair Classifiers from Linear Post-Processing. - Ruicheng Xian; Han Zhao 002 (CoRR, 2024)

LibMOON: A Gradient-based MultiObjective OptimizatioN Library in PyTorch. - Xiaoyuan Zhang; Liang Zhao; Yingying Yu; Xi Lin 001; Zhenkun Wang 001; Han Zhao 002; Qingfu Zhang 001 (CoRR, 2024)

Transforming the Hybrid Cloud for Emerging AI Workloads. - 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; et al. (CoRR, 2024)

A survey of recent methods for addressing AI fairness and bias in biomedicine. - Yifan Yang 006; Mingquan Lin; Han Zhao 002; Yifan Peng 002; Furong Huang; Zhiyong Lu (J. Biomed. Informatics, 2024)

Efficient Modality Selection in Multimodal Learning. - Yifei He; Runxiang Cheng; Gargi Balasubramaniam; Yao-Hung Hubert Tsai; Han Zhao 002 (J. Mach. Learn. Res., 2024)

Enhancing Compositional Generalization via Compositional Feature Alignment. - Haoxiang Wang 003; Haozhe Si; Huajie Shao; Han Zhao 002 (Trans. Mach. Learn. Res., 2024)

RLHF Workflow: From Reward Modeling to Online RLHF. - Hanze Dong; Wei Xiong 015; Bo Pang 004; Haoxiang Wang 003; Han Zhao 002; Yingbo Zhou; Nan Jiang 008; Doyen Sahoo; Caiming Xiong; Tong Zhang 001 (Trans. Mach. Learn. Res., 2024)

A General-Purpose Multi-Modal OOD Detection Framework. - Viet Duong; Qiong Wu 008; Zhengyi Zhou; Eric Zavesky; Wen-Ling Hsu; Han Zhao 002; Huajie Shao (Trans. Mach. Learn. Res., 2024)

Personalized Federated Learning with Spurious Features: An Adversarial Approach. - Xiaoyang Wang; Han Zhao 002; Klara Nahrstedt; Sanmi Koyejo (Trans. Mach. Learn. Res., 2024)

Self-Supervised Learning across the Spectrum. - Jayanth Shenoy; Xingjian Davis Zhang; Bill Tao; Shlok Mehrotra; Rem Yang; Han Zhao 002; Deepak Vasisht (Remote. Sens., 2024)

Scaling Laws for Multilingual Language Models. - Yifei He; Alon Benhaim; Barun Patra; Praneetha Vaddamanu; Sanchit Ahuja; Parul Chopra; Vishrav Chaudhary; Han Zhao 002; Xia Song (ACL (Findings), 2025)

Learning Structured Representations by Embedding Class Hierarchy with Fast Optimal Transport. - Siqi Zeng 001; Sixian Du; Makoto Yamada; Han Zhao 002 (ICLR, 2025)

Accelerating Neural ODEs: A Variational Formulation-based Approach. - Hongjue Zhao; Yuchen Wang; Hairong Qi 001; Zijie Huang 002; Han Zhao 002; Lui Sha; Huajie Shao (ICLR, 2025)

Towards Understanding the Fragility of Multilingual LLMs against Fine-Tuning Attacks. - Samuele Poppi; Zheng-Xin Yong; Yifei He; Bobbie Chern; Han Zhao 002; Aobo Yang; Jianfeng Chi (NAACL (Findings), 2025)

Moment Alignment: Unifying Gradient and Hessian Matching for Domain Generalization. - Yuen Chen; Haozhe Si; Guojun Zhang; Han Zhao 002 (UAI, 2025)

Localize-and-Stitch: Efficient Model Merging via Sparse Task Arithmetic. - Yifei He; Yuzheng Hu; Yong Lin; Tong Zhang 001; Han Zhao 002 (Trans. Mach. Learn. Res., 2025)

Neural Probabilistic Circuits: Enabling Compositional and Interpretable Predictions through Logical Reasoning. - Weixin Chen; Simon Yu; Huajie Shao; Lui Sha; Han Zhao 002 (CoRR, 2025)

Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond. - Weiyu Chen; Xiaoyuan Zhang; Baijiong Lin; Xi Lin 001; Han Zhao 002; Qingfu Zhang 001; James T. Kwok (CoRR, 2025)

Efficient Model Editing with Task Vector Bases: A Theoretical Framework and Scalable Approach. - Siqi Zeng 001; Yifei He; Weiqiu You; Yifan Hao 002; Yao-Hung Hubert Tsai; Makoto Yamada; Han Zhao 002 (CoRR, 2025)

Towards Scalable Foundation Model for Multi-modal and Hyperspectral Geospatial Data. - Haozhe Si; Yuxuan Wan; Minh Do; Deepak Vasisht; Han Zhao 002; Hendrik F. Hamann (CoRR, 2025)

MergeBench: A Benchmark for Merging Domain-Specialized LLMs. - Yifei He; Siqi Zeng 001; Yuzheng Hu; Rui Yang 010; Tong Zhang 001; Han Zhao 002 (CoRR, 2025)

GraSS: Scalable Influence Function with Sparse Gradient Compression. - Pingbang Hu; Joseph Melkonian; Weijing Tang; Han Zhao 002; Jiaqi W. Ma (CoRR, 2025)

MiCRo: Mixture Modeling and Context-aware Routing for Personalized Preference Learning. - Jingyan Shen; Jiarui Yao; Rui Yang 010; Yifan Sun; Feng Luo; Rui Pan 002; Tong Zhang 001; Han Zhao 002 (CoRR, 2025)

S2Edit: Text-Guided Image Editing with Precise Semantic and Spatial Control. - Xudong Liu; Zikun Chen; Ruowei Jiang; Ziyi Wu; Kejia Yin; Han Zhao 002; Parham Aarabi; Igor Gilitschenski (CoRR, 2025)