受强制性开放获取政策约束的文章 - Chun Kai Ling了解详情
可在其他位置公开访问的文章：8 篇
Gaussian process planning with Lipschitz continuous reward functions: Towards unifying Bayesian optimization, active learning, and beyond
CK Ling, KH Low, P Jaillet
Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016
强制性开放获取政策： National Research Foundation, Singapore
Correlation in extensive-form games: Saddle-point formulation and benchmarks
G Farina, CK Ling, F Fang, T Sandholm
Advances in Neural Information Processing Systems 32, 2019
强制性开放获取政策： US National Science Foundation, US Department of Defense
Efficient regret minimization algorithm for extensive-form correlated equilibrium
G Farina, CK Ling, F Fang, T Sandholm
Advances in Neural Information Processing Systems 32, 2019
强制性开放获取政策： US National Science Foundation, US Department of Defense
Multi-defender Security Games with Schedules
Z Song, CK Ling, F Fang
International Conference on Decision and Game Theory for Security, 65-85, 2023
强制性开放获取政策： US National Science Foundation, US Department of Defense
Function approximation for solving stackelberg equilibrium in large perfect information games
CK Ling, JZ Kolter, F Fang
Proceedings of the AAAI Conference on Artificial Intelligence 37 (5), 5764-5772, 2023
强制性开放获取政策： US National Science Foundation
Safe Subgame Resolving for Extensive Form Correlated Equilibrium
CK Ling, F Fang
Proceedings of the AAAI Conference on Artificial Intelligence 36 (5), 5116-5123, 2022
强制性开放获取政策： US National Science Foundation
Power of Correlation in Extensive-Form Games
G Farina, CK Ling, F Fang, T Sandholm
IJCAI Workshop on Strategic Reasoning, 2019
强制性开放获取政策： US National Science Foundation
Gaussian Process Planning with Lipschitz Continuous Reward Functions
CK Ling, KH Low, P Jaillet
Association for Computing Machinery, 2016
强制性开放获取政策： National Research Foundation, Singapore
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