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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, 4882-4892, 2021
204*2021
Spiderboost and momentum: Faster variance reduction algorithms
Z Wang, K Ji, Y Zhou, Y Liang, V Tarokh
Advances in Neural Information Processing Systems 32, 2019
1672019
Provably faster algorithms for bilevel optimization
J Yang, K Ji, Y Liang
Advances in Neural Information Processing Systems 34, 13670-13682, 2021
1072021
Spiderboost: A class of faster variance-reduced algorithms for nonconvex optimization
Z Wang, K Ji, Y Zhou, Y Liang, V Tarokh
arXiv 2018, 2018
812018
Theoretical Convergence of Multi-Step Model-Agnostic Meta-Learning.
K Ji, J Yang, Y Liang
Journal of Machine Learning Research 23, 29:1-29:41, 2022
76*2022
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 33, 11490-11500, 2020
622020
Improved zeroth-order variance reduced algorithms and analysis for nonconvex optimization
K Ji, Z Wang, Y Zhou, Y Liang
International conference on machine learning, 3100-3109, 2019
612019
Lower Bounds and Accelerated Algorithms for Bilevel Optimization
K Ji, Y Liang
Journal of Machine Learning Research (JMLR) 24, 22:1-22:56, 2023
51*2023
A new one-point residual-feedback oracle for black-box learning and control
Y Zhang, Y Zhou, K Ji, MM Zavlanos
Automatica 136, 110006, 2022
44*2022
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
412022
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 34 (04), 4036-4043, 2020
292020
Will bilevel optimizers benefit from loops
K Ji, M Liu, Y Liang, L Ying
Advances in Neural Information Processing Systems 35, 3011-3023, 2022
252022
When will gradient methods converge to max‐margin classifier under ReLU models?
T Xu, Y Zhou, K Ji, Y Liang
Stat 10 (1), e354, 2021
23*2021
On resource pooling and separation for lru caching
J Tan, G Quan, K Ji, N Shroff
SIGMETRICS 2018 2 (1), 5, 2018
232018
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, 4762-4772, 2020
20*2020
Efficiently escaping saddle points in bilevel optimization
M Huang, K Ji, S Ma, L Lai
arXiv preprint arXiv:2202.03684, 2022
192022
On the convergence theory for hessian-free bilevel algorithms
D Sow, K Ji, Y Liang
Advances in Neural Information Processing Systems 35, 4136-4149, 2022
17*2022
Understanding estimation and generalization error of generative adversarial networks
K Ji, Y Zhou, Y Liang
IEEE Transactions on Information Theory 67 (5), 3114-3129, 2021
162021
Momentum schemes with stochastic variance reduction for nonconvex composite optimization
Y Zhou, Z Wang, K Ji, Y Liang, V Tarokh
arXiv preprint arXiv:1902.02715, 2019
132019
Asymptotic miss ratio of LRU caching with consistent hashing
K Ji, G Quan, J Tan
IEEE INFOCOM 2018-IEEE Conference on Computer Communications, 450-458, 2018
122018
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