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Kaiyi Ji
Kaiyi Ji
Assistant Professor at University at Buffalo
Verified email at buffalo.edu - Homepage
Title
Cited by
Cited by
Year
Bilevel optimization: Convergence analysis and enhanced design
K Ji, J Yang, Y Liang
International Conference on Machine Learning (ICML), 2021
300*2021
Spiderboost and momentum: Faster variance reduction algorithms
Z Wang, K Ji, Y Zhou, Y Liang, V Tarokh
Advances in Neural Information Processing Systems (NeurIPS), 2019
1992019
Provably faster algorithms for bilevel optimization
J Yang, K Ji, Y Liang
Advances in Neural Information Processing Systems (NeurIPS Spotlight), 2021
1482021
Theoretical convergence of multi-step model-agnostic meta-learning
K Ji, J Yang, Y Liang
Journal of machine learning research (JMLR), 2022
98*2022
Spiderboost: A class of faster variance-reduced algorithms for nonconvex optimization
Z Wang, K Ji, Y Zhou, Y Liang, V Tarokh
arXiv 2018, 2018
882018
Convergence of meta-learning with task-specific adaptation over partial parameters
K Ji, JD Lee, Y Liang, HV Poor
Advances in Neural Information Processing Systems (NeurIPS), 2020
842020
Improved zeroth-order variance reduced algorithms and analysis for nonconvex optimization
K Ji, Z Wang, Y Zhou, Y Liang
International conference on machine learning (ICML), 2019
842019
Lower Bounds and Accelerated Algorithms for Bilevel Optimization
K Ji, Y Liang
Journal of Machine Learning Research (JMLR), 2023
62*2023
A primal-dual approach to bilevel optimization with multiple inner minima
D Sow, K Ji, Z Guan, Y Liang
arXiv preprint arXiv:2203.01123, 2022
602022
A new one-point residual-feedback oracle for black-box learning and control
Y Zhang, Y Zhou, K Ji, MM Zavlanos
Automatica, 2022
56*2022
Will bilevel optimizers benefit from loops
K Ji, M Liu, Y Liang, L Ying
Advances in Neural Information Processing Systems (NeurIPS Spotlight), 2022
392022
Robust stochastic bandit algorithms under probabilistic unbounded adversarial attack
Z Guan, K Ji, DJ Bucci Jr, TY Hu, J Palombo, M Liston, Y Liang
Proceedings of the AAAI Conference on Artificial Intelligence (AAAI Spotlight), 2020
362020
On the convergence theory for hessian-free bilevel algorithms
D Sow, K Ji, Y Liang
Advances in Neural Information Processing Systems (NeurIPS), 2022
31*2022
Efficiently escaping saddle points in bilevel optimization
M Huang, X Chen, K Ji, S Ma, L Lai
Journal of Machine Learning Research (JMLR), 2025
272025
When will gradient methods converge to max‐margin classifier under ReLU models?
T Xu, Y Zhou, K Ji, Y Liang
Stat, Special Issue of Deep Learning from Statistical Perspective, 2021
24*2021
On resource pooling and separation for lru caching
J Tan, G Quan, K Ji, N Shroff
SIGMETRICS 2018, 2018
242018
History-gradient aided batch size adaptation for variance reduced algorithms
K Ji, Z Wang, B Weng, Y Zhou, W Zhang, Y Liang
International Conference on Machine Learning (ICML), 2020
23*2020
Understanding estimation and generalization error of generative adversarial networks
K Ji, Y Zhou, Y Liang
IEEE Transactions on Information Theory (TIT), 2021
222021
Direction-oriented multi-objective learning: Simple and provable stochastic algorithms
P Xiao, H Ban, K Ji
Advances in Neural Information Processing Systems (NeurIPS), 2024
202024
Achieving linear speedup in non-iid federated bilevel learning
M Huang, D Zhang, K Ji
International Conference on Machine Learning (ICML), 2023
182023
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