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Chung-Wei Lee
Chung-Wei Lee
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Title
Cited by
Cited by
Year
Multi-label zero-shot learning with structured knowledge graphs
CW Lee, W Fang, CK Yeh, YCF Wang
Proceedings of the IEEE conference on computer vision and pattern …, 2018
3302018
A new algorithm for non-stationary contextual bandits: Efficient, optimal and parameter-free
Y Chen, CW Lee, H Luo, CY Wei
Conference on Learning Theory, 696-726, 2019
1282019
Linear Last-iterate Convergence in Constrained Saddle-point Optimization
CY Wei, CW Lee, M Zhang, H Luo
International Conference on Learning Representations, 2021
1102021
Last-iterate convergence of decentralized optimistic gradient descent/ascent in infinite-horizon competitive markov games
CY Wei, CW Lee, M Zhang, H Luo
Conference on learning theory, 4259-4299, 2021
972021
Bias no more: high-probability data-dependent regret bounds for adversarial bandits and MDPs
CW Lee, H Luo, CY Wei, M Zhang
Advances in Neural Information Processing Systems 33, 15522-15533, 2020
582020
Policy optimization in adversarial mdps: Improved exploration via dilated bonuses
H Luo, CY Wei, CW Lee
Advances in Neural Information Processing Systems 34, 22931-22942, 2021
472021
Achieving near instance-optimality and minimax-optimality in stochastic and adversarial linear bandits simultaneously
CW Lee, H Luo, CY Wei, M Zhang, X Zhang
International Conference on Machine Learning, 6142-6151, 2021
462021
Last-iterate convergence in extensive-form games
CW Lee, C Kroer, H Luo
Advances in Neural Information Processing Systems 34, 14293-14305, 2021
402021
Near-optimal no-regret learning for general convex games
G Farina, I Anagnostides, H Luo, CW Lee, C Kroer, T Sandholm
Advances in Neural Information Processing Systems 35, 2022
322022
Uncoupled Learning Dynamics with Swap Regret in Multiplayer Games
I Anagnostides, G Farina, C Kroer, CW Lee, H Luo, T Sandholm
Advances in Neural Information Processing Systems 35, 2022
302022
Achieving optimal dynamic regret for non-stationary bandits without prior information
P Auer, Y Chen, P Gajane, CW Lee, H Luo, R Ortner, CY Wei
Conference on Learning Theory, 159-163, 2019
302019
Kernelized multiplicative weights for 0/1-polyhedral games: Bridging the gap between learning in extensive-form and normal-form games
G Farina, CW Lee, H Luo, C Kroer
International Conference on Machine Learning, 6337-6357, 2022
272022
A closer look at small-loss bounds for bandits with graph feedback
CW Lee, H Luo, M Zhang
Conference on Learning Theory, 2516-2564, 2020
222020
Linear last-iterate convergence for matrix games and stochastic games
CW Lee, H Luo, CY Wei, M Zhang
arXiv e-prints, arXiv: 2006.09517, 2020
162020
Clairvoyant Regret Minimization: Equivalence with Nemirovski's Conceptual Prox Method and Extension to General Convex Games
G Farina, C Kroer, CW Lee, H Luo
NeurIPS 2022 Workshop on Optimization for Machine Learning, 2022
62022
Regret matching+:(in) stability and fast convergence in games
G Farina, J Grand-Clément, C Kroer, CW Lee, H Luo
Advances in Neural Information Processing Systems 36, 2024
52024
Context-lumpable stochastic bandits
CW Lee, Q Liu, Y Abbasi Yadkori, C Jin, T Lattimore, C Szepesvári
Advances in Neural Information Processing Systems 36, 2024
22024
Fast Last-Iterate Convergence of Learning in Games Requires Forgetful Algorithms
Y Cai, G Farina, J Grand-Clément, C Kroer, CW Lee, H Luo, W Zheng
arXiv preprint arXiv:2406.10631, 2024
12024
Last-Iterate Convergence Properties of Regret-Matching Algorithms in Games
Y Cai, G Farina, J Grand-Clément, C Kroer, CW Lee, H Luo, W Zheng
arXiv preprint arXiv:2311.00676, 2023
2023
Practical Knowledge Distillation: Using DNNs to Beat DNNs
CW Lee, PA Apostolopulos, IL Markov
arXiv preprint arXiv:2302.12360, 2023
2023
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Articles 1–20