On Kernelized Multi-armed Bandits

3 April 2017

Papers citing "On Kernelized Multi-armed Bandits"

50 / 117 papers shown

Title
Game-theoretic statistics and safe anytime-valid inference Aaditya Ramdas Peter Grünwald V. Vovk Glenn Shafer 40 119 0 04 Oct 2022
Batch Bayesian optimisation via density-ratio estimation with guarantees Rafael Oliveira Louis C. Tiao Fabio Ramos 47 7 0 22 Sep 2022
A Nonparametric Contextual Bandit with Arm-level Eligibility Control for Customer Service Routing Ruofeng Wen Wenjun Zeng Yi Liu 26 0 0 08 Sep 2022
Event-Triggered Time-Varying Bayesian Optimization Paul Brunzema Alexander von Rohr Friedrich Solowjow Sebastian Trimpe 21 7 0 23 Aug 2022
Bayesian Optimization with Informative Covariance Afonso Eduardo Michael U. Gutmann 24 3 0 04 Aug 2022
Exploration in Linear Bandits with Rich Action Sets and its Implications for Inference Debangshu Banerjee Avishek Ghosh Sayak Ray Chowdhury Aditya Gopalan 35 9 0 23 Jul 2022
Collaborative Learning in Kernel-based Bandits for Distributed Users Sudeep Salgia Sattar Vakili Qing Zhao FedML 39 6 0 16 Jul 2022
Graph Neural Network Bandits Parnian Kassraie Andreas Krause Ilija Bogunovic 26 11 0 13 Jul 2022
Computationally Efficient PAC RL in POMDPs with Latent Determinism and Conditional Embeddings Masatoshi Uehara Ayush Sekhari Jason D. Lee Nathan Kallus Wen Sun 60 6 0 24 Jun 2022
Surrogate modeling for Bayesian optimization beyond a single Gaussian process Qin Lu Konstantinos D. Polyzos Bingcong Li G. Giannakis GP 22 18 0 27 May 2022
Adjusted Expected Improvement for Cumulative Regret Minimization in Noisy Bayesian Optimization Shouri Hu Haowei Wang Zhongxiang Dai K. H. Low Szu Hui Ng 33 4 0 10 May 2022
Provably Efficient Kernelized Q-Learning Shuang Liu H. Su MLT 27 4 0 21 Apr 2022
Instance-Dependent Regret Analysis of Kernelized Bandits S. Shekhar T. Javidi 27 3 0 12 Mar 2022
Fast online inference for nonlinear contextual bandit based on Generative Adversarial Network Yun-Da Tsai Shou-De Lin 46 5 0 17 Feb 2022
Efficient Kernel UCB for Contextual Bandits Houssam Zenati A. Bietti Eustache Diemert Julien Mairal Matthieu Martin Pierre Gaillard 24 3 0 11 Feb 2022
Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning Sattar Vakili Jonathan Scarlett Da-shan Shiu A. Bernacchia 33 18 0 08 Feb 2022
GoSafeOpt: Scalable Safe Exploration for Global Optimization of Dynamical Systems Bhavya Sukhija M. Turchetta David Lindner Andreas Krause Sebastian Trimpe Dominik Baumann 31 17 0 24 Jan 2022
Misspecified Gaussian Process Bandit Optimization Ilija Bogunovic Andreas Krause 57 42 0 09 Nov 2021
Risk-averse Heteroscedastic Bayesian Optimization A. Makarova Ilnura N. Usmanova Ilija Bogunovic Andreas Krause 16 35 0 05 Nov 2021
Empirical analysis of representation learning and exploration in neural kernel bandits Michal Lisicki Arash Afkanpour Graham W. Taylor 18 0 0 05 Nov 2021
Nearly Optimal Algorithms for Level Set Estimation Blake Mason Romain Camilleri Subhojyoti Mukherjee Kevin G. Jamieson Robert D. Nowak Lalit P. Jain 30 22 0 02 Nov 2021
Collaborative Pure Exploration in Kernel Bandit Yihan Du Wei Chen Yuko Kuroki Longbo Huang 40 10 0 29 Oct 2021
Differentially Private Federated Bayesian Optimization with Distributed Exploration Zhongxiang Dai K. H. Low Patrick Jaillet FedML 18 41 0 27 Oct 2021
Safe Policy Learning through Extrapolation: Application to Pre-trial Risk Assessment Eli Ben-Michael D. J. Greiner Kosuke Imai Zhichao Jiang OffRL 33 22 0 22 Sep 2021
Gaussian Process Uniform Error Bounds with Unknown Hyperparameters for Safety-Critical Applications A. Capone Armin Lederer Sandra Hirche 32 18 0 06 Sep 2021
Optimal Order Simple Regret for Gaussian Process Bandits Sattar Vakili N. Bouziani Sepehr Jalali A. Bernacchia Da-shan Shiu 34 51 0 20 Aug 2021
Efficient Model-Based Multi-Agent Mean-Field Reinforcement Learning Barna Pásztor Ilija Bogunovic Andreas Krause 28 41 0 08 Jul 2021
Neural Active Learning with Performance Guarantees Pranjal Awasthi Christoph Dann Claudio Gentile Ayush Sekhari Zhilei Wang 32 22 0 06 Jun 2021
Bayesian Optimistic Optimisation with Exponentially Decaying Regret Hung The Tran Sunil R. Gupta Santu Rana Svetha Venkatesh 16 3 0 10 May 2021
Learning-enhanced robust controller synthesis with rigorous statistical and control-theoretic guarantees Christian Fiedler C. Scherer Sebastian Trimpe 24 15 0 07 May 2021
Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression Christian Fiedler C. Scherer Sebastian Trimpe GP 26 65 0 06 May 2021
Distributed Bayesian Online Learning for Cooperative Manipulation P. B. G. Dohmann Armin Lederer Marcel Dissemond Sandra Hirche OffRL 19 5 0 09 Apr 2021
Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning Sebastian Curi Ilija Bogunovic Andreas Krause 39 17 0 18 Mar 2021
No-Regret Algorithms for Private Gaussian Process Bandit Optimization Abhimanyu Dubey 22 13 0 24 Feb 2021
Is Pessimism Provably Efficient for Offline RL? Ying Jin Zhuoran Yang Zhaoran Wang OffRL 27 349 0 30 Dec 2020
Policy Optimization as Online Learning with Mediator Feedback Alberto Maria Metelli Matteo Papini P. DÓro Marcello Restelli OffRL 27 10 0 15 Dec 2020
Gaussian Process-based Min-norm Stabilizing Controller for Control-Affine Systems with Uncertain Input Effects and Dynamics F. Castañeda Jason J. Choi Bike Zhang Claire Tomlin Koushil Sreenath 34 38 0 14 Nov 2020
On Function Approximation in Reinforcement Learning: Optimism in the Face of Large State Spaces Zhuoran Yang Chi Jin Zhaoran Wang Mengdi Wang Michael I. Jordan 39 18 0 09 Nov 2020
Local Differential Privacy for Bayesian Optimization Xingyu Zhou Jian Tan 16 24 0 13 Oct 2020
Neural Thompson Sampling Weitong Zhang Dongruo Zhou Lihong Li Quanquan Gu 34 115 0 02 Oct 2020
Mean-Variance Analysis in Bayesian Optimization under Uncertainty S. Iwazaki Yu Inatsu Ichiro Takeuchi 34 33 0 17 Sep 2020
On Information Gain and Regret Bounds in Gaussian Process Bandits Sattar Vakili Kia Khezeli Victor Picheny GP 25 128 0 15 Sep 2020
IntelligentPooling: Practical Thompson Sampling for mHealth Sabina Tomkins Peng Liao P. Klasnja S. Murphy 34 30 0 31 Jul 2020
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning Sebastian Curi Felix Berkenkamp Andreas Krause 33 82 0 15 Jun 2020
Scalable Thompson Sampling using Sparse Gaussian Process Models Sattar Vakili Henry B. Moss A. Artemev Vincent Dutordoir Victor Picheny 13 34 0 09 Jun 2020
An Efficient Algorithm For Generalized Linear Bandit: Online Stochastic Gradient Descent and Thompson Sampling Qin Ding Cho-Jui Hsieh James Sharpnack 25 37 0 07 Jun 2020
Bayesian optimization for modular black-box systems with switching costs Chi-Heng Lin Joseph D. Miano Eva L. Dyer 8 5 0 04 Jun 2020
Corruption-Tolerant Gaussian Process Bandit Optimization Ilija Bogunovic Andreas Krause Jonathan Scarlett 30 51 0 04 Mar 2020
Information Directed Sampling for Linear Partial Monitoring Johannes Kirschner Tor Lattimore Andreas Krause 24 46 0 25 Feb 2020
Rapidly Personalizing Mobile Health Treatment Policies with Limited Data Sabina Tomkins Peng Liao P. Klasnja Serena Yeung S. Murphy 44 6 0 23 Feb 2020