Ji, Kaiyi

31 publications

JMLR 2025 Efficiently Escaping Saddle Points in Bilevel Optimization Minhui Huang, Xuxing Chen, Kaiyi Ji, Shiqian Ma, Lifeng Lai

AAAI 2025 First-Order Federated Bilevel Learning Yifan Yang, Peiyao Xiao, Shiqian Ma, Kaiyi Ji

ICLR 2025 MGDA Converges Under Generalized Smoothness, Provably Qi Zhang, Peiyao Xiao, Shaofeng Zou, Kaiyi Ji

ICCV 2025 SAMO: A Lightweight Sharpness-Aware Approach for Multi-Task Optimization with Joint Global-Local Perturbation Hao Ban, Gokul Ram Subramani, Kaiyi Ji

ICLR 2025 Tuning-Free Bilevel Optimization: New Algorithms and Convergence Analysis Yifan Yang, Hao Ban, Minhui Huang, Shiqian Ma, Kaiyi Ji

TMLR 2025 Understanding Fine-Tuning in Approximate Unlearning: A Theoretical Perspective Meng Ding, Rohan Sharma, Changyou Chen, Jinhui Xu, Kaiyi Ji

ICLR 2024 AUC-CL: A Batchsize-Robust Framework for Self-Supervised Contrastive Representation Learning Rohan Sharma, Kaiyi Ji, Zhiqiang Xu, Changyou Chen

ICML 2024 Fair Resource Allocation in Multi-Task Learning Hao Ban, Kaiyi Ji

NeurIPS 2024 First-Order Minimax Bilevel Optimization Yifan Yang, Zhaofeng Si, Siwei Lyu, Kaiyi Ji

ICML 2024 Understanding Forgetting in Continual Learning with Linear Regression Meng Ding, Kaiyi Ji, Di Wang, Jinhui Xu

NeurIPS 2023 Achieving $\mathcal{O}(\epsilon^{-1.5})$ Complexity in Hessian/Jacobian-Free Stochastic Bilevel Optimization Yifan Yang, Peiyao Xiao, Kaiyi Ji

ICML 2023 Achieving Linear Speedup in Non-IID Federated Bilevel Learning Minhui Huang, Dewei Zhang, Kaiyi Ji

NeurIPS 2023 Bilevel Coreset Selection in Continual Learning: A New Formulation and Algorithm Jie Hao, Kaiyi Ji, Mingrui Liu

ICML 2023 Communication-Efficient Federated Hypergradient Computation via Aggregated Iterative Differentiation Peiyao Xiao, Kaiyi Ji

NeurIPS 2023 Direction-Oriented Multi-Objective Learning: Simple and Provable Stochastic Algorithms Peiyao Xiao, Hao Ban, Kaiyi Ji

JMLR 2023 Lower Bounds and Accelerated Algorithms for Bilevel Optimization Kaiyi Ji, Yingbin Liang

NeurIPS 2023 Non-Convex Bilevel Optimization with Time-Varying Objective Functions Sen Lin, Daouda Sow, Kaiyi Ji, Yingbin Liang, Ness Shroff

NeurIPS 2023 SimFBO: Towards Simple, Flexible and Communication-Efficient Federated Bilevel Learning Yifan Yang, Peiyao Xiao, Kaiyi Ji

UAI 2022 Data Sampling Affects the Complexity of Online SGD over Dependent Data Shaocong Ma, Ziyi Chen, Yi Zhou, Kaiyi Ji, Yingbin Liang

NeurIPS 2022 On the Convergence Theory for Hessian-Free Bilevel Algorithms Daouda Sow, Kaiyi Ji, Yingbin Liang

JMLR 2022 Theoretical Convergence of Multi-Step Model-Agnostic Meta-Learning Kaiyi Ji, Junjie Yang, Yingbin Liang

NeurIPS 2022 Will Bilevel Optimizers Benefit from Loops Kaiyi Ji, Mingrui Liu, Yingbin Liang, Lei Ying

ICML 2021 Bilevel Optimization: Convergence Analysis and Enhanced Design Kaiyi Ji, Junjie Yang, Yingbin Liang

NeurIPS 2021 Provably Faster Algorithms for Bilevel Optimization Junjie Yang, Kaiyi Ji, Yingbin Liang

NeurIPS 2020 Convergence of Meta-Learning with Task-Specific Adaptation over Partial Parameters Kaiyi Ji, Jason Lee, Yingbin Liang, H. Vincent Poor

ICML 2020 History-Gradient Aided Batch Size Adaptation for Variance Reduced Algorithms Kaiyi Ji, Zhe Wang, Bowen Weng, Yi Zhou, Wei Zhang, Yingbin Liang

IJCAI 2020 Proximal Gradient Algorithm with Momentum and Flexible Parameter Restart for Nonconvex Optimization Yi Zhou, Zhe Wang, Kaiyi Ji, Yingbin Liang, Vahid Tarokh

AAAI 2020 Robust Stochastic Bandit Algorithms Under Probabilistic Unbounded Adversarial Attack Ziwei Guan, Kaiyi Ji, Donald J. Bucci Jr., Timothy Y. Hu, Joseph Palombo, Michael Liston, Yingbin Liang

ICML 2019 Improved Zeroth-Order Variance Reduced Algorithms and Analysis for Nonconvex Optimization Kaiyi Ji, Zhe Wang, Yi Zhou, Yingbin Liang

NeurIPS 2019 SpiderBoost and Momentum: Faster Variance Reduction Algorithms Zhe Wang, Kaiyi Ji, Yi Zhou, Yingbin Liang, Vahid Tarokh

NeurIPS 2018 Minimax Estimation of Neural Net Distance Kaiyi Ji, Yingbin Liang