Papers citing 'Gaussian Process Bandit Optimization with Few Batches'

Title
Robust Batched Bandits Yunwen Guo Yunlun Shu Gongyi Zhuo Tianyu Wang 8 0 0 04 Oct 2025
Improved Regret Bounds for Gaussian Process Upper Confidence Bound in Bayesian Optimization Shogo Iwazaki GP 135 1 0 02 Jun 2025
Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds Aya Kayal Sattar Vakili Laura Toni Da-shan Shiu A. Bernacchia 112 0 0 29 May 2025
Distributionally Robust Active Learning for Gaussian Process Regression Shion Takeno Yoshito Okura Yu Inatsu Aoyama Tatsuya Tomonari Tanaka ... Noriaki Hashimoto Taro Murayama Hanju Lee Shinya Kojima Ichiro Takeuchi OOD GP 185 0 0 24 Feb 2025
Improved Regret Analysis in Gaussian Process Bandits: Optimality for Noiseless Reward, RKHS norm, and Non-Stationary Variance S. Iwazaki Shion Takeno 175 4 0 10 Feb 2025
Differentially Private Kernelized Contextual Bandits Nikola Pavlovic Sudeep Salgia Qing Zhao 139 3 0 13 Jan 2025
Constrained Multi-objective Bayesian Optimization through Optimistic Constraints Estimation Diantong Li Fengxue Zhang Chong Liu Yuxin Chen 644 1 0 06 Nov 2024
Lower Bounds for Time-Varying Kernelized Bandits Xu Cai Jonathan Scarlett 143 1 0 22 Oct 2024
The Traveling Bandit: A Framework for Bayesian Optimization with Movement Costs Qiyuan Chen Raed Al Kontar 151 1 0 18 Oct 2024
Batched Stochastic Bandit for Nondegenerate Functions Yu Liu Yunlu Shu Tianyu Wang 318 1 0 09 May 2024
Random Exploration in Bayesian Optimization: Order-Optimal Regret and Computational Efficiency Sudeep Salgia Sattar Vakili Qing Zhao 123 12 0 23 Oct 2023
Kernelized Reinforcement Learning with Order Optimal Regret Bounds Sattar Vakili Julia Olkhovskaya 154 10 0 13 Jun 2023
From Random Search to Bandit Learning in Metric Measure Spaces Chuying Han Yasong Feng Tianyu Wang 166 3 0 19 May 2023
Sample Complexity of Kernel-Based Q-Learning Sing-Yuan Yeh Fu-Chieh Chang Chang-Wei Yueh Pei-Yuan Wu A. Bernacchia Sattar Vakili OffRL 127 5 0 01 Feb 2023
Regret Bounds for Noise-Free Cascaded Kernelized Bandits Zihan Li Jonathan Scarlett 106 2 0 10 Nov 2022
Benefits of Monotonicity in Safe Exploration with Gaussian Processes Arpan Losalka Jonathan Scarlett 129 1 0 03 Nov 2022
Graph Neural Network Bandits Parnian Kassraie Andreas Krause Ilija Bogunovic 144 12 0 13 Jul 2022
Bayesian Optimization under Stochastic Delayed Feedback Arun Verma Zhongxiang Dai Bryan Kian Hsiang Low 114 15 0 19 Jun 2022
Provably and Practically Efficient Neural Contextual Bandits Sudeep Salgia Sattar Vakili Qing Zhao 122 10 0 31 May 2022
On Kernelized Multi-Armed Bandits with Constraints Xingyu Zhou Bo Ji 121 33 0 29 Mar 2022
Instance-Dependent Regret Analysis of Kernelized Bandits S. Shekhar T. Javidi 94 4 0 12 Mar 2022
Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning Sattar Vakili Jonathan Scarlett Da-shan Shiu A. Bernacchia 157 20 0 08 Feb 2022
A Robust Phased Elimination Algorithm for Corruption-Tolerant Gaussian Process Bandits Ilija Bogunovic Zihan Li Andreas Krause Jonathan Scarlett 166 9 0 03 Feb 2022
Collaborative Pure Exploration in Kernel Bandit Yihan Du Wei Chen Yuko Kuroki Longbo Huang 218 12 0 29 Oct 2021
Open Problem: Tight Online Confidence Intervals for RKHS Elements Sattar Vakili John Scarlett T. Javidi 124 22 0 28 Oct 2021
Lipschitz Bandits with Batched Feedback Yasong Feng Zengfeng Huang Tianyu Wang 231 16 0 19 Oct 2021
Adversarial Attacks on Gaussian Process Bandits E. Han Jonathan Scarlett GP AAML 146 7 0 16 Oct 2021
Multi-Scale Zero-Order Optimization of Smooth Functions in an RKHS S. Shekhar T. Javidi 87 20 0 11 May 2020
Regret Bounds for Noise-Free Kernel-Based Bandits Sattar Vakili 161 8 0 12 Feb 2020