$PyXAB -- A Python Library for $\mathcal{X}$-Armed Bandit and Online Blackbox Optimization Algorithms$

PyXAB -- A Python Library for $\mathcal{X}$ -Armed Bandit and Online Blackbox Optimization Algorithms

7 March 2023

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Papers citing "PyXAB -- A Python Library for $\mathcal{X}$-Armed Bandit and Online Blackbox Optimization Algorithms"

6 / 6 papers shown

Title
Parameter-Free Algorithms for Performative Regret Minimization under Decision-Dependent Distributions Sungwoo Park Junyeop Kwon Byeongnoh Kim Suhyun Chae Jeeyong Lee Dabeen Lee 79 0 0 23 Feb 2024
Personalized Federated X -armed Bandit Wenjie Li Qifan Song Jean Honorio 23 0 0 25 Oct 2023
Approximating Nash Equilibria in Normal-Form Games via Stochastic Optimization I. Gemp Luke Marris Georgios Piliouras 81 9 0 10 Oct 2023
Robust Lipschitz Bandits to Adversarial Corruptions Yue Kang Cho-Jui Hsieh T. C. Lee AAML 98 10 0 29 May 2023
Federated X-Armed Bandit Wenjie Li Qifan Song Jean Honorio Guang Lin FedML 113 4 0 30 May 2022
Optimum-statistical Collaboration Towards General and Efficient Black-box Optimization Wenjie Li ChiHua Wang Guang Cheng Qifan Song 112 8 0 17 Jun 2021