Kaiyi Ji - RankMe

89 papers A* 27A 1B 1Journal 58Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	DeepMTL2R: A Library for Deep Multi-task Learning to Rank. CoRR Chaosheng Dong, Peiyao Xiao, Yijia Wang, Kaiyi Ji
2026	J	`jnl`	Provable Effects of Data Replay in Continual Learning: A Feature Learning Perspective. CoRR Meng Ding, Jinhui Xu, Kaiyi Ji
2025	J	`jnl`	Efficiently Escaping Saddle Points in Bilevel Optimization. J. Mach. Learn. Res. Minhui Huang, Xuxing Chen, Kaiyi Ji, Shiqian Ma, Lifeng Lai
2025	A*	`conf`	First-Order Federated Bilevel Learning. AAAI Yifan Yang, Peiyao Xiao, Shiqian Ma, Kaiyi Ji
2025	J	`jnl`	Lower Complexity Bounds for Nonconvex-Strongly-Convex Bilevel Optimization with First-Order Oracles. CoRR Kaiyi Ji
2025	A*	`conf`	MGDA Converges under Generalized Smoothness, Provably. ICLR Qi Zhang, Peiyao Xiao, Shaofeng Zou, Kaiyi Ji
2025	J	`jnl`	ReGNet: Reciprocal Space-Aware Long-Range Modeling and Multi-Property Prediction for Crystals. CoRR Jianan Nie, Peiyao Xiao, Kaiyi Ji, Peng Gao
2025	J	`jnl`	Rethinking Parameter Sharing for LLM Fine-Tuning with Multiple LoRAs. CoRR Hao Ban, Kaiyi Ji
2025	J	`jnl`	SAMO: A Lightweight Sharpness-Aware Approach for Multi-Task Optimization with Joint Global-Local Perturbation. CoRR Hao Ban, Gokul Ram Subramani, Kaiyi Ji
2025	J	`jnl`	Scalable Bilevel Loss Balancing for Multi-Task Learning. CoRR Peiyao Xiao, Chaosheng Dong, Shaofeng Zou, Kaiyi Ji
2025	J	`jnl`	Task-Agnostic Continual Prompt Tuning with Gradient-Based Selection and Decoding. CoRR Anushka Tiwari, Sayantan Pal, Rohini K. Srihari, Kaiyi Ji
2025	J	`jnl`	Theoretical Study of Conflict-Avoidant Multi-Objective Reinforcement Learning. IEEE Trans. Inf. Theory Yudan Wang, Peiyao Xiao, Hao Ban, Kaiyi Ji, Shaofeng Zou
2025	A*	`conf`	Tuning-Free Bilevel Optimization: New Algorithms and Convergence Analysis. ICLR Yifan Yang, Hao Ban, Minhui Huang, Shiqian Ma, Kaiyi Ji
2025	J	`jnl`	Understanding Fine-tuning in Approximate Unlearning: A Theoretical Perspective. Trans. Mach. Learn. Res. Meng Ding, Rohan Sharma, Changyou Chen, Jinhui Xu, Kaiyi Ji
2024	A*	`conf`	AUC-CL: A Batchsize-Robust Framework for Self-Supervised Contrastive Representation Learning. ICLR Rohan Sharma, Kaiyi Ji, Zhiqiang Xu, Changyou Chen
2024	J	`jnl`	Boosting One-Point Derivative-Free Online Optimization via Residual Feedback. IEEE Trans. Autom. Control. Yan Zhang, Yi Zhou, Kaiyi Ji, Yi Shen, Michael M. Zavlanos
2024	J	`jnl`	Discriminative Adversarial Unlearning. CoRR Rohan Sharma, Shijie Zhou, Kaiyi Ji, Changyou Chen
2024	J	`jnl`	Enhancing Diffusion Posterior Sampling for Inverse Problems by Integrating Crafted Measurements. CoRR Shijie Zhou, Huaisheng Zhu, Rohan Sharma, Ruiyi Zhang, Kaiyi Ji, Changyou Chen
2024	A*	`conf`	Fair Resource Allocation in Multi-Task Learning. ICML Hao Ban, Kaiyi Ji
2024	J	`jnl`	Fair Resource Allocation in Multi-Task Learning. CoRR Hao Ban, Kaiyi Ji
2024	J	`jnl`	Finite-Time Analysis for Conflict-Avoidant Multi-Task Reinforcement Learning. CoRR Yudan Wang, Peiyao Xiao, Hao Ban, Kaiyi Ji, Shaofeng Zou
2024	A*	`conf`	First-Order Minimax Bilevel Optimization. NeurIPS Yifan Yang, Zhaofeng Si, Siwei Lyu, Kaiyi Ji
2024	J	`jnl`	Imperative Learning: A Self-supervised Neural-Symbolic Learning Framework for Robot Autonomy. CoRR 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
2024	J	`jnl`	Meta-Learning with Heterogeneous Tasks. CoRR Zhaofeng Si, Shu Hu, Kaiyi Ji, Siwei Lyu
2024	J	`jnl`	On the Convergence of Multi-objective Optimization under Generalized Smoothness. CoRR Qi Zhang, Peiyao Xiao, Kaiyi Ji, Shaofeng Zou
2024	J	`jnl`	Tuning-Free Bilevel Optimization: New Algorithms and Convergence Analysis. CoRR Yifan Yang, Hao Ban, Minhui Huang, Shiqian Ma, Kaiyi Ji
2024	A*	`conf`	Understanding Forgetting in Continual Learning with Linear Regression. ICML Meng Ding, Kaiyi Ji, Di Wang, Jinhui Xu
2024	J	`jnl`	Understanding Forgetting in Continual Learning with Linear Regression. CoRR Meng Ding, Kaiyi Ji, Di Wang, Jinhui Xu
2024	J	`jnl`	Why Fine-Tuning Struggles with Forgetting in Machine Unlearning? Theoretical Insights and a Remedial Approach. CoRR Meng Ding, Jinhui Xu, Kaiyi Ji
2023	A*	`conf`	Achieving Linear Speedup in Non-IID Federated Bilevel Learning. ICML Minhui Huang, Dewei Zhang, Kaiyi Ji
2023	J	`jnl`	Achieving Linear Speedup in Non-IID Federated Bilevel Learning. CoRR Minhui Huang, Dewei Zhang, Kaiyi Ji
2023	A*	`conf`	Achieving O(ε NeurIPS Yifan Yang, Peiyao Xiao, Kaiyi Ji
2023	J	`jnl`	Achieving O(ε CoRR Yifan Yang, Peiyao Xiao, Kaiyi Ji
2023	A*	`conf`	Bilevel Coreset Selection in Continual Learning: A New Formulation and Algorithm. NeurIPS Jie Hao, Kaiyi Ji, Mingrui Liu
2023	A*	`conf`	Communication-Efficient Federated Hypergradient Computation via Aggregated Iterative Differentiation. ICML Peiyao Xiao, Kaiyi Ji
2023	J	`jnl`	Communication-Efficient Federated Hypergradient Computation via Aggregated Iterative Differentiation. CoRR Peiyao Xiao, Kaiyi Ji
2023	A*	`conf`	Direction-oriented Multi-objective Learning: Simple and Provable Stochastic Algorithms. NeurIPS Peiyao Xiao, Hao Ban, Kaiyi Ji
2023	J	`jnl`	Direction-oriented Multi-objective Learning: Simple and Provable Stochastic Algorithms. CoRR Peiyao Xiao, Hao Ban, Kaiyi Ji
2023	J	`jnl`	Lower Bounds and Accelerated Algorithms for Bilevel Optimization. J. Mach. Learn. Res. Kaiyi Ji, Yingbin Liang
2023	B	`conf`	Network Utility Maximization with Unknown Utility Functions: A Distributed, Data-Driven Bilevel Optimization Approach. MobiHoc Kaiyi Ji, Lei Ying
2023	J	`jnl`	Network Utility Maximization with Unknown Utility Functions: A Distributed, Data-Driven Bilevel Optimization Approach. CoRR Kaiyi Ji, Lei Ying
2023	A*	`conf`	Non-Convex Bilevel Optimization with Time-Varying Objective Functions. NeurIPS Sen Lin, Daouda Sow, Kaiyi Ji, Yingbin Liang, Ness B. Shroff
2023	J	`jnl`	Non-Convex Bilevel Optimization with Time-Varying Objective Functions. CoRR Sen Lin, Daouda Sow, Kaiyi Ji, Yingbin Liang, Ness B. Shroff
2023	A*	`conf`	SimFBO: Towards Simple, Flexible and Communication-efficient Federated Bilevel Learning. NeurIPS Yifan Yang, Peiyao Xiao, Kaiyi Ji
2023	J	`jnl`	SimFBO: Towards Simple, Flexible and Communication-efficient Federated Bilevel Learning. CoRR Yifan Yang, Peiyao Xiao, Kaiyi Ji
2022	J	`jnl`	A Constrained Optimization Approach to Bilevel Optimization with Multiple Inner Minima. CoRR Daouda Sow, Kaiyi Ji, Ziwei Guan, Yingbin Liang
2022	J	`jnl`	A new one-point residual-feedback oracle for black-box learning and control. Autom. Yan Zhang, Yi Zhou, Kaiyi Ji, Michael M. Zavlanos
2022	J	`jnl`	Data Sampling Affects the Complexity of Online SGD over Dependent Data. CoRR Shaocong Ma, Ziyi Chen, Yi Zhou, Kaiyi Ji, Yingbin Liang
2022	A	`conf`	Data sampling affects the complexity of online SGD over dependent data. UAI Shaocong Ma, Ziyi Chen, Yi Zhou, Kaiyi Ji, Yingbin Liang
2022	J	`jnl`	Efficiently Escaping Saddle Points in Bilevel Optimization. CoRR Minhui Huang, Kaiyi Ji, Shiqian Ma, Lifeng Lai
2022	A*	`conf`	On the Convergence Theory for Hessian-Free Bilevel Algorithms. NeurIPS Daouda Sow, Kaiyi Ji, Yingbin Liang
2022	J	`jnl`	Theoretical Convergence of Multi-Step Model-Agnostic Meta-Learning. J. Mach. Learn. Res. Kaiyi Ji, Junjie Yang, Yingbin Liang
2022	A*	`conf`	Will Bilevel Optimizers Benefit from Loops. NeurIPS Kaiyi Ji, Mingrui Liu, Yingbin Liang, Lei Ying
2022	J	`jnl`	Will Bilevel Optimizers Benefit from Loops. CoRR Kaiyi Ji, Mingrui Liu, Yingbin Liang, Lei Ying
2021	J	`jnl`	Bilevel Optimization for Machine Learning: Algorithm Design and Convergence Analysis. CoRR Kaiyi Ji
2021	A*	`conf`	Bilevel Optimization: Convergence Analysis and Enhanced Design. ICML Kaiyi Ji, Junjie Yang, Yingbin Liang
2021	J	`jnl`	ES-Based Jacobian Enables Faster Bilevel Optimization. CoRR Daouda Sow, Kaiyi Ji, Yingbin Liang
2021	J	`jnl`	Lower Bounds and Accelerated Algorithms for Bilevel Optimization. CoRR Kaiyi Ji, Yingbin Liang
2021	A*	`conf`	Provably Faster Algorithms for Bilevel Optimization. NeurIPS Junjie Yang, Kaiyi Ji, Yingbin Liang
2021	J	`jnl`	Provably Faster Algorithms for Bilevel Optimization. CoRR Junjie Yang, Kaiyi Ji, Yingbin Liang
2021	J	`jnl`	Understanding Estimation and Generalization Error of Generative Adversarial Networks. IEEE Trans. Inf. Theory Kaiyi Ji, Yi Zhou, Yingbin Liang
2020	J	`jnl`	Boosting One-Point Derivative-Free Online Optimization via Residual Feedback. CoRR Yan Zhang, Yi Zhou, Kaiyi Ji, Michael M. Zavlanos
2020	A*	`conf`	Convergence of Meta-Learning with Task-Specific Adaptation over Partial Parameters. NeurIPS Kaiyi Ji, Jason D. Lee, Yingbin Liang, H. Vincent Poor
2020	J	`jnl`	Convergence of Meta-Learning with Task-Specific Adaptation over Partial Parameters. CoRR Kaiyi Ji, Jason D. Lee, Yingbin Liang, H. Vincent Poor
2020	A*	`conf`	History-Gradient Aided Batch Size Adaptation for Variance Reduced Algorithms. ICML Kaiyi Ji, Zhe Wang, Bowen Weng, Yi Zhou, Wei Zhang, Yingbin Liang
2020	J	`jnl`	Improving the Convergence Rate of One-Point Zeroth-Order Optimization using Residual Feedback. CoRR Yan Zhang, Yi Zhou, Kaiyi Ji, Michael M. Zavlanos
2020	J	`jnl`	Learning Latent Features With Pairwise Penalties in Low-Rank Matrix Completion. IEEE Trans. Signal Process. Kaiyi Ji, Jian Tan, Jinfeng Xu, Yuejie Chi
2020	—	`conf`	Learning Latent Features with Pairwise Penalties in Low-Rank Matrix Completion. SAM Kaiyi Ji, Jian Tan, Jinfeng Xu, Yuejie Chi
2020	J	`jnl`	Multi-Step Model-Agnostic Meta-Learning: Convergence and Improved Algorithms. CoRR Kaiyi Ji, Junjie Yang, Yingbin Liang
2020	J	`jnl`	Provably Faster Algorithms for Bilevel Optimization and Applications to Meta-Learning. CoRR Kaiyi Ji, Junjie Yang, Yingbin Liang
2020	A*	`conf`	Proximal Gradient Algorithm with Momentum and Flexible Parameter Restart for Nonconvex Optimization. IJCAI Yi Zhou, Zhe Wang, Kaiyi Ji, Yingbin Liang, Vahid Tarokh
2020	J	`jnl`	Proximal Gradient Algorithm with Momentum and Flexible Parameter Restart for Nonconvex Optimization. CoRR Yi Zhou, Zhe Wang, Kaiyi Ji, Yingbin Liang, Vahid Tarokh
2020	A*	`conf`	Robust Stochastic Bandit Algorithms under Probabilistic Unbounded Adversarial Attack. AAAI Ziwei Guan, Kaiyi Ji, Donald J. Bucci Jr., Timothy Y. Hu, Joseph Palombo, Michael Liston, Yingbin Liang
2020	J	`jnl`	Robust Stochastic Bandit Algorithms under Probabilistic Unbounded Adversarial Attack. CoRR Ziwei Guan, Kaiyi Ji, Donald J. Bucci Jr., Timothy Y. Hu, Joseph Palombo, Michael Liston, Yingbin Liang
2019	J	`jnl`	Faster Stochastic Algorithms via History-Gradient Aided Batch Size Adaptation. CoRR Kaiyi Ji, Zhe Wang, Yi Zhou, Yingbin Liang
2019	A*	`conf`	Improved Zeroth-Order Variance Reduced Algorithms and Analysis for Nonconvex Optimization. ICML Kaiyi Ji, Zhe Wang, Yi Zhou, Yingbin Liang
2019	J	`jnl`	Improved Zeroth-Order Variance Reduced Algorithms and Analysis for Nonconvex Optimization. CoRR Kaiyi Ji, Zhe Wang, Yi Zhou, Yingbin Liang
2019	A*	`conf`	SpiderBoost and Momentum: Faster Variance Reduction Algorithms. NeurIPS Zhe Wang, Kaiyi Ji, Yi Zhou, Yingbin Liang, Vahid Tarokh
2018	A*	`conf`	Asymptotic Miss Ratio of LRU Caching with Consistent Hashing. INFOCOM Kaiyi Ji, Guocong Quan, Jian Tan
2018	J	`jnl`	Asymptotic Miss Ratio of LRU Caching with Consistent Hashing. CoRR Kaiyi Ji, Guocong Quan, Jian Tan
2018	J	`jnl`	Convergence of SGD in Learning ReLU Models with Separable Data. CoRR Tengyu Xu, Yi Zhou, Kaiyi Ji, Yingbin Liang
2018	A*	`conf`	LRU Caching with Dependent Competing Requests. INFOCOM Guocong Quan, Kaiyi Ji, Jian Tan
2018	J	`jnl`	Learning Latent Features with Pairwise Penalties in Matrix Completion. CoRR Kaiyi Ji, Jian Tan, Yuejie Chi, Jinfeng Xu
2018	A*	`conf`	Minimax Estimation of Neural Net Distance. NeurIPS Kaiyi Ji, Yingbin Liang
2018	J	`jnl`	Minimax Estimation of Neural Net Distance. CoRR Kaiyi Ji, Yingbin Liang
2018	—	`conf`	On Resource Pooling and Separation for LRU Caching. SIGMETRICS (Abstracts) Jian Tan, Guocong Quan, Kaiyi Ji, Ness B. Shroff
2018	J	`jnl`	On Resource Pooling and Separation for LRU Caching. Proc. ACM Meas. Anal. Comput. Syst. Jian Tan, Guocong Quan, Kaiyi Ji, Ness B. Shroff
2018	J	`jnl`	SpiderBoost: A Class of Faster Variance-reduced Algorithms for Nonconvex Optimization. CoRR Zhe Wang, Kaiyi Ji, Yi Zhou, Yingbin Liang, Vahid Tarokh
2017	J	`jnl`	On Resource Pooling and Separation for LRU Caching. CoRR Jian Tan, Guocong Quan, Kaiyi Ji, Ness B. Shroff