Li, Tian

27 publications

AAAI 2025 AI-Powered Algorithm-Centric Quantum Processor Topology Design Tian Li, Xiao-Yue Xu, Chen Ding, Tian-Ci Tian, Wei-You Liao, Shuo Zhang, He-Liang Huang

NeurIPS 2025 Efficient Adaptive Federated Optimization Su Hyeong Lee, Sidharth Sharma, Manzil Zaheer, Tian Li

ICML 2025 Efficient Distributed Optimization Under Heavy-Tailed Noise Su Hyeong Lee, Manzil Zaheer, Tian Li

ICLRW 2025 Efficient Distributed Optimization Under Heavy-Tailed Noise Su Hyeong Lee, Manzil Zaheer, Tian Li

ICML 2025 Generalization and Robustness of the Tilted Empirical Risk Gholamali Aminian, Amir R. Asadi, Tian Li, Ahmad Beirami, Gesine Reinert, Samuel N. Cohen

ICLR 2025 Many-Objective Multi-Solution Transport Ziyue Li, Tian Li, Virginia Smith, Jeff Bilmes, Tianyi Zhou

ICLRW 2025 Private Retrieval Augmented Generation with Random Projection Dixi Yao, Tian Li

NeurIPS 2025 Private Zeroth-Order Optimization with Public Data Xuchen Gong, Tian Li

AAAI 2025 Scalable and Trustworthy Learning in Heterogeneous Networks Tian Li

ICML 2025 Tilted Sharpness-Aware Minimization Tian Li, Tianyi Zhou, Jeff Bilmes

ICMLW 2024 Efficient Adaptive Federated Optimization Su Hyeong Lee, Sidharth Sharma, Manzil Zaheer, Tian Li

TMLR 2024 Maximizing Global Model Appeal in Federated Learning Yae Jee Cho, Divyansh Jhunjhunwala, Tian Li, Virginia Smith, Gauri Joshi

ICLR 2023 Differentially Private Adaptive Optimization with Delayed Preconditioners Tian Li, Manzil Zaheer, Ken Liu, Sashank J. Reddi, Hugh Brendan McMahan, Virginia Smith

JMLR 2023 On Tilted Losses in Machine Learning: Theory and Applications Tian Li, Ahmad Beirami, Maziar Sanjabi, Virginia Smith

NeurIPSW 2022 Differentially Private Adaptive Optimization with Delayed Preconditioners Tian Li, Manzil Zaheer, Ken Liu, Sashank J. Reddi, Hugh Brendan McMahan, Virginia Smith

ICLR 2022 Diverse Client Selection for Federated Learning via Submodular Maximization Ravikumar Balakrishnan, Tian Li, Tianyi Zhou, Nageen Himayat, Virginia Smith, Jeff Bilmes

IJCAI 2022 Domain-Adaptive Text Classification with Structured Knowledge from Unlabeled Data Tian Li, Xiang Chen, Zhen Dong, Kurt Keutzer, Shanghang Zhang

NeurIPSW 2022 Motley: Benchmarking Heterogeneity and Personalization in Federated Learning Shanshan Wu, Tian Li, Zachary Charles, Yu Xiao, Ken Liu, Zheng Xu, Virginia Smith

ECCV 2022 PreTraM: Self-Supervised Pre-Training via Connecting Trajectory and mAP Chenfeng Xu, Tian Li, Chen Tang, Lingfeng Sun, Kurt Keutzer, Masayoshi Tomizuka, Alireza Fathi, Wei Zhan

ICML 2022 Private Adaptive Optimization with Side Information Tian Li, Manzil Zaheer, Sashank Reddi, Virginia Smith

NeurIPSW 2022 To Federate or Not to Federate: Incentivizing Client Participation in Federated Learning Yae Jee Cho, Divyansh Jhunjhunwala, Tian Li, Virginia Smith, Gauri Joshi

ICML 2021 Ditto: Fair and Robust Federated Learning Through Personalization Tian Li, Shengyuan Hu, Ahmad Beirami, Virginia Smith

NeurIPS 2021 Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing Mikhail Khodak, Renbo Tu, Tian Li, Liam Li, Maria-Florina F Balcan, Virginia Smith, Ameet Talwalkar

ICML 2021 Heterogeneity for the Win: One-Shot Federated Clustering Don Kurian Dennis, Tian Li, Virginia Smith

ICLR 2021 Tilted Empirical Risk Minimization Tian Li, Ahmad Beirami, Maziar Sanjabi, Virginia Smith

ICLR 2020 Fair Resource Allocation in Federated Learning Tian Li, Maziar Sanjabi, Ahmad Beirami, Virginia Smith

ICMLW 2019 Federated Optimization for Heterogeneous Networks Tian Li, Anit Kumar Sahu, Manzil Zaheer, Maziar Sanjabi, Ameet Talwalkar, Virginia Smith