Chun Kai Ling
Title
Cited by
Cited by
Year
Gaussian process planning with Lipschitz continuous reward functions: Towards unifying Bayesian optimization, active learning, and beyond
CK Ling, KH Low, P Jaillet
Thirtieth AAAI Conference on Artificial Intelligence, 2016
552016
What game are we playing? end-to-end learning in normal and extensive form games
CK Ling, F Fang, JZ Kolter
arXiv preprint arXiv:1805.02777, 2018
462018
Large scale learning of agent rationality in two-player zero-sum games
CK Ling, F Fang, JZ Kolter
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 6104-6111, 2019
142019
Correlation in extensive-form games: Saddle-point formulation and benchmarks
G Farina, CK Ling, F Fang, T Sandholm
arXiv preprint arXiv:1905.12564, 2019
142019
Efficient regret minimization algorithm for extensive-form correlated equilibrium
G Farina, CK Ling, F Fang, T Sandholm
arXiv preprint arXiv:1910.12450, 2019
72019
Nonmyopic Gaussian process optimization with macro-actions
D Kharkovskii, CK Ling, BKH Low
International Conference on Artificial Intelligence and Statistics, 4593-4604, 2020
62020
Deep Archimedean Copulas
CK Ling, F Fang, JZ Kolter
arXiv preprint arXiv:2012.03137, 2020
12020
Safe Search for Stackelberg Equilibria in Extensive-Form Games
CK Ling, N Brown
Proceedings of the AAAI Conference on Artificial Intelligence 35 (6), 5541-5548, 2021
2021
Power of Correlation in Extensive-Form Games
G Farina, CK Ling, F Fang, T Sandholm
IJCAI Workshop on Strategic Reasoning, 2019
2019
Gaussian Process Planning with Lipschitz Continuous Reward Functions
CK Ling, KH Low, P Jaillet
Association for Computing Machinery, 2016
2016
Learning Attacker Utilities in Nested-Logit Security Games
CK Ling, H Oh
Scoring Rules for Adaptive Multi-stage Questions
CK Ling, G Manek
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Articles 1–12