Kaiyi Ji

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 67

Top Topics

Convex Optimization

Top Venues

J. Mach. Learn. Res.

Publications

Qi Zhang, Peiyao Xiao, Kaiyi Ji, Shaofeng Zou
On the Convergence of Multi-objective Optimization under Generalized Smoothness. CoRR (2024)
Rohan Sharma, Kaiyi Ji, Zhiqiang Xu, Changyou Chen
AUC-CL: A Batchsize-Robust Framework for Self-Supervised Contrastive Representation Learning. ICLR (2024)
Yudan Wang, Peiyao Xiao, Hao Ban, Kaiyi Ji, Shaofeng Zou
Finite-Time Analysis for Conflict-Avoidant Multi-Task Reinforcement Learning. CoRR (2024)
Chen Wang, Kaiyi Ji, Junyi Geng, Zhongqiang Ren, Taimeng Fu, Fan Yang, Yifan Guo, Haonan He, Xiangyu Chen, Zitong Zhan, Qiwei Du, Shaoshu Su, Bowen Li, Yuheng Qiu, Yi Du, Qihang Li, Yifan Yang, Xiao Lin, Zhipeng Zhao
Imperative Learning: A Self-supervised Neural-Symbolic Learning Framework for Robot Autonomy. CoRR (2024)
Rohan Sharma, Shijie Zhou, Kaiyi Ji, Changyou Chen
Discriminative Adversarial Unlearning. CoRR (2024)
Meng Ding, Kaiyi Ji, Di Wang, Jinhui Xu
Understanding Forgetting in Continual Learning with Linear Regression. CoRR (2024)
Hao Ban, Kaiyi Ji
Fair Resource Allocation in Multi-Task Learning. CoRR (2024)
Minhui Huang, Dewei Zhang, Kaiyi Ji
Achieving Linear Speedup in Non-IID Federated Bilevel Learning. ICML (2023)
Yifan Yang, Peiyao Xiao, Kaiyi Ji
) Complexity in Hessian/Jacobian-free Stochastic Bilevel Optimization. CoRR (2023)
Yifan Yang, Peiyao Xiao, Kaiyi Ji
SimFBO: Towards Simple, Flexible and Communication-efficient Federated Bilevel Learning. CoRR (2023)
Kaiyi Ji, Lei Ying
Network Utility Maximization with Unknown Utility Functions: A Distributed, Data-Driven Bilevel Optimization Approach. CoRR (2023)
Peiyao Xiao, Hao Ban, Kaiyi Ji
Direction-oriented Multi-objective Learning: Simple and Provable Stochastic Algorithms. NeurIPS (2023)
Peiyao Xiao, Kaiyi Ji
Communication-Efficient Federated Hypergradient Computation via Aggregated Iterative Differentiation. CoRR (2023)
Peiyao Xiao, Hao Ban, Kaiyi Ji
Direction-oriented Multi-objective Learning: Simple and Provable Stochastic Algorithms. CoRR (2023)
Kaiyi Ji, Lei Ying
Network Utility Maximization with Unknown Utility Functions: A Distributed, Data-Driven Bilevel Optimization Approach. MobiHoc (2023)
Minhui Huang, Dewei Zhang, Kaiyi Ji
Achieving Linear Speedup in Non-IID Federated Bilevel Learning. CoRR (2023)
Yifan Yang, Peiyao Xiao, Kaiyi Ji
) Complexity in Hessian/Jacobian-free Stochastic Bilevel Optimization. NeurIPS (2023)
Sen Lin, Daouda Sow, Kaiyi Ji, Yingbin Liang, Ness B. Shroff
Non-Convex Bilevel Optimization with Time-Varying Objective Functions. CoRR (2023)
Jie Hao, Kaiyi Ji, Mingrui Liu
Bilevel Coreset Selection in Continual Learning: A New Formulation and Algorithm. NeurIPS (2023)
Peiyao Xiao, Kaiyi Ji
Communication-Efficient Federated Hypergradient Computation via Aggregated Iterative Differentiation. ICML (2023)
Yifan Yang, Peiyao Xiao, Kaiyi Ji
SimFBO: Towards Simple, Flexible and Communication-efficient Federated Bilevel Learning. NeurIPS (2023)
Sen Lin, Daouda Sow, Kaiyi Ji, Yingbin Liang, Ness B. Shroff
Non-Convex Bilevel Optimization with Time-Varying Objective Functions. NeurIPS (2023)
Kaiyi Ji, Yingbin Liang
Lower Bounds and Accelerated Algorithms for Bilevel Optimization. J. Mach. Learn. Res. 24 (2023)
Yan Zhang, Yi Zhou, Kaiyi Ji, Michael M. Zavlanos
A new one-point residual-feedback oracle for black-box learning and control. Autom. 136 (2022)
Kaiyi Ji, Junjie Yang, Yingbin Liang
Theoretical Convergence of Multi-Step Model-Agnostic Meta-Learning. J. Mach. Learn. Res. 23 (2022)
Daouda Sow, Kaiyi Ji, Yingbin Liang
On the Convergence Theory for Hessian-Free Bilevel Algorithms. NeurIPS (2022)
Kaiyi Ji, Mingrui Liu, Yingbin Liang, Lei Ying
Will Bilevel Optimizers Benefit from Loops. NeurIPS (2022)
Daouda Sow, Kaiyi Ji, Ziwei Guan, Yingbin Liang
A Constrained Optimization Approach to Bilevel Optimization with Multiple Inner Minima. CoRR (2022)
Shaocong Ma, Ziyi Chen, Yi Zhou, Kaiyi Ji, Yingbin Liang
Data Sampling Affects the Complexity of Online SGD over Dependent Data. CoRR (2022)
Minhui Huang, Kaiyi Ji, Shiqian Ma, Lifeng Lai
Efficiently Escaping Saddle Points in Bilevel Optimization. CoRR (2022)
Shaocong Ma, Ziyi Chen, Yi Zhou, Kaiyi Ji, Yingbin Liang
Data sampling affects the complexity of online SGD over dependent data. UAI (2022)
Kaiyi Ji, Mingrui Liu, Yingbin Liang, Lei Ying
Will Bilevel Optimizers Benefit from Loops. CoRR (2022)
Kaiyi Ji
Bilevel Optimization for Machine Learning: Algorithm Design and Convergence Analysis. CoRR (2021)
Kaiyi Ji, Junjie Yang, Yingbin Liang
Bilevel Optimization: Convergence Analysis and Enhanced Design. ICML (2021)
Junjie Yang, Kaiyi Ji, Yingbin Liang
Provably Faster Algorithms for Bilevel Optimization. CoRR (2021)
Kaiyi Ji, Yingbin Liang
Lower Bounds and Accelerated Algorithms for Bilevel Optimization. CoRR (2021)
Daouda Sow, Kaiyi Ji, Yingbin Liang
ES-Based Jacobian Enables Faster Bilevel Optimization. CoRR (2021)
Junjie Yang, Kaiyi Ji, Yingbin Liang
Provably Faster Algorithms for Bilevel Optimization. NeurIPS (2021)
Kaiyi Ji, Yi Zhou, Yingbin Liang
Understanding Estimation and Generalization Error of Generative Adversarial Networks. IEEE Trans. Inf. Theory 67 (5) (2021)
Kaiyi Ji, Junjie Yang, Yingbin Liang
Provably Faster Algorithms for Bilevel Optimization and Applications to Meta-Learning. CoRR (2020)
Kaiyi Ji, Jason D. Lee, Yingbin Liang, H. Vincent Poor
Convergence of Meta-Learning with Task-Specific Adaptation over Partial Parameters. CoRR (2020)
Kaiyi Ji, Junjie Yang, Yingbin Liang
Multi-Step Model-Agnostic Meta-Learning: Convergence and Improved Algorithms. CoRR (2020)
Kaiyi Ji, Jian Tan, Jinfeng Xu, Yuejie Chi
Learning Latent Features With Pairwise Penalties in Low-Rank Matrix Completion. IEEE Trans. Signal Process. 68 (2020)
Kaiyi Ji, Zhe Wang, Bowen Weng, Yi Zhou, Wei Zhang, Yingbin Liang
History-Gradient Aided Batch Size Adaptation for Variance Reduced Algorithms. ICML (2020)
Yi Zhou, Zhe Wang, Kaiyi Ji, Yingbin Liang, Vahid Tarokh
Proximal Gradient Algorithm with Momentum and Flexible Parameter Restart for Nonconvex Optimization. IJCAI (2020)
Ziwei Guan, Kaiyi Ji, Donald J. Bucci Jr., Timothy Y. Hu, Joseph Palombo, Michael Liston, Yingbin Liang
Robust Stochastic Bandit Algorithms under Probabilistic Unbounded Adversarial Attack. CoRR (2020)
Yan Zhang, Yi Zhou, Kaiyi Ji, Michael M. Zavlanos
Improving the Convergence Rate of One-Point Zeroth-Order Optimization using Residual Feedback. CoRR (2020)
Kaiyi Ji, Jason D. Lee, Yingbin Liang, H. Vincent Poor
Convergence of Meta-Learning with Task-Specific Adaptation over Partial Parameters. NeurIPS (2020)
Yan Zhang, Yi Zhou, Kaiyi Ji, Michael M. Zavlanos
Boosting One-Point Derivative-Free Online Optimization via Residual Feedback. CoRR (2020)
Kaiyi Ji, Jian Tan, Jinfeng Xu, Yuejie Chi
Learning Latent Features with Pairwise Penalties in Low-Rank Matrix Completion. SAM (2020)
Yi Zhou, Zhe Wang, Kaiyi Ji, Yingbin Liang, Vahid Tarokh
Proximal Gradient Algorithm with Momentum and Flexible Parameter Restart for Nonconvex Optimization. CoRR (2020)
Ziwei Guan, Kaiyi Ji, Donald J. Bucci Jr., Timothy Y. Hu, Joseph Palombo, Michael Liston, Yingbin Liang
Robust Stochastic Bandit Algorithms under Probabilistic Unbounded Adversarial Attack. AAAI (2020)
Kaiyi Ji, Zhe Wang, Yi Zhou, Yingbin Liang
Improved Zeroth-Order Variance Reduced Algorithms and Analysis for Nonconvex Optimization. ICML (2019)
Kaiyi Ji, Zhe Wang, Yi Zhou, Yingbin Liang
Faster Stochastic Algorithms via History-Gradient Aided Batch Size Adaptation. CoRR (2019)
Kaiyi Ji, Zhe Wang, Yi Zhou, Yingbin Liang
Improved Zeroth-Order Variance Reduced Algorithms and Analysis for Nonconvex Optimization. CoRR (2019)
Zhe Wang, Kaiyi Ji, Yi Zhou, Yingbin Liang, Vahid Tarokh
SpiderBoost and Momentum: Faster Variance Reduction Algorithms. NeurIPS (2019)
Jian Tan, Guocong Quan, Kaiyi Ji, Ness B. Shroff
On Resource Pooling and Separation for LRU Caching. SIGMETRICS (Abstracts) (2018)
Kaiyi Ji, Yingbin Liang
Minimax Estimation of Neural Net Distance. NeurIPS (2018)
Zhe Wang, Kaiyi Ji, Yi Zhou, Yingbin Liang, Vahid Tarokh
SpiderBoost: A Class of Faster Variance-reduced Algorithms for Nonconvex Optimization. CoRR (2018)
Kaiyi Ji, Guocong Quan, Jian Tan
Asymptotic Miss Ratio of LRU Caching with Consistent Hashing. CoRR (2018)
Jian Tan, Guocong Quan, Kaiyi Ji, Ness B. Shroff
On Resource Pooling and Separation for LRU Caching. Proc. ACM Meas. Anal. Comput. Syst. 2 (1) (2018)
Tengyu Xu, Yi Zhou, Kaiyi Ji, Yingbin Liang
Convergence of SGD in Learning ReLU Models with Separable Data. CoRR (2018)
Guocong Quan, Kaiyi Ji, Jian Tan
LRU Caching with Dependent Competing Requests. INFOCOM (2018)
Kaiyi Ji, Guocong Quan, Jian Tan
Asymptotic Miss Ratio of LRU Caching with Consistent Hashing. INFOCOM (2018)
Kaiyi Ji, Jian Tan, Yuejie Chi, Jinfeng Xu
Learning Latent Features with Pairwise Penalties in Matrix Completion. CoRR (2018)
Kaiyi Ji, Yingbin Liang
Minimax Estimation of Neural Net Distance. CoRR (2018)
Jian Tan, Guocong Quan, Kaiyi Ji, Ness B. Shroff
On Resource Pooling and Separation for LRU Caching. CoRR (2017)