Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

21 December 2009

Papers citing "Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design"

50 / 617 papers shown

Title
No-PASt-BO: Normalized Portfolio Allocation Strategy for Bayesian Optimization Thiago de P. Vasconcelos Daniel Augusto R. M. A. de Souza C. L. C. Mattos Joao P. P. Gomes 17 11 0 01 Aug 2019
High Dimensional Bayesian Optimization via Supervised Dimension Reduction Miao Zhang Huiqi Li Steven W. Su 27 44 0 21 Jul 2019
Exploration Through Reward Biasing: Reward-Biased Maximum Likelihood Estimation for Stochastic Multi-Armed Bandits Xi Liu Ping-Chun Hsieh A. Bhattacharya P. R. Kumar 11 0 0 02 Jul 2019
Adaptive Pricing in Insurance: Generalized Linear Models and Gaussian Process Regression Approaches Yuqing Zhang N. Walton 21 3 0 02 Jul 2019
Deep Active Learning with Adaptive Acquisition Manuel Haussmann Fred Hamprecht M. Kandemir 22 41 0 27 Jun 2019
Bayesian Optimization with Directionally Constrained Search Yongqian Li Yaqiang Yao 6 3 0 22 Jun 2019
Split Q Learning: Reinforcement Learning with Two-Stream Rewards Baihan Lin Djallel Bouneffouf Guillermo Cecchi OffRL 14 22 0 21 Jun 2019
Region of Attraction for Power Systems using Gaussian Process and Converse Lyapunov Function -- Part I: Theoretical Framework and Off-line Study Chao Zhai H. Nguyen 21 10 0 09 Jun 2019
Stochastic Bandits with Context Distributions Johannes Kirschner Andreas Krause 29 30 0 06 Jun 2019
Posterior Variance Analysis of Gaussian Processes with Application to Average Learning Curves Armin Lederer Jonas Umlauft Sandra Hirche 14 25 0 04 Jun 2019
Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control Armin Lederer Jonas Umlauft Sandra Hirche 11 150 0 04 Jun 2019
Multi-objective Bayesian Optimization using Pareto-frontier Entropy Shinya Suzuki Shion Takeno T. Tamura Kazuki Shitara Masayuki Karasuyama 33 73 0 01 Jun 2019
DEEP-BO for Hyperparameter Optimization of Deep Networks Hyunghun Cho Yongjin Kim Eunjung Lee Daeyoung Choi Yongjae Lee Wonjong Rhee 16 1 0 23 May 2019
Evolving Rewards to Automate Reinforcement Learning Aleksandra Faust Anthony G. Francis Dar Mehta 31 50 0 18 May 2019
Bayesian Optimization for Polynomial Time Probabilistically Complete STL Trajectory Synthesis Vince Kurtz Hai Lin 12 2 0 08 May 2019
Lipschitz Bandit Optimization with Improved Efficiency Xu Zhu 24 1 0 25 Apr 2019
Stochastic Lipschitz Q-Learning Xu Zhu 22 4 0 24 Apr 2019
Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design Kevin Kaichuang Yang Yuxin Chen Alycia Lee Yisong Yue 35 16 0 17 Apr 2019
Introduction to Multi-Armed Bandits Aleksandrs Slivkins 28 990 0 15 Apr 2019
A Note on the Equivalence of Upper Confidence Bounds and Gittins Indices for Patient Agents Daniel Russo 16 8 0 09 Apr 2019
Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization Michael Volpp Lukas P. Frohlich Kirsten Fischer Andreas Doerr Stefan Falkner Frank Hutter Christian Daniel 26 84 0 04 Apr 2019
Sampling Acquisition Functions for Batch Bayesian Optimization Alessandro De Palma Celestine Mendler-Dünner Thomas Parnell Andreea Anghel H. Pozidis 39 13 0 22 Mar 2019
Active learning for enumerating local minima based on Gaussian process derivatives Yu Inatsu Daisuke Sugita K. Toyoura Ichiro Takeuchi 23 6 0 08 Mar 2019
Learning to Plan in High Dimensions via Neural Exploration-Exploitation Trees Binghong Chen Bo Dai Qinjie Lin Guo Ye Han Liu Le Song 29 51 0 28 Feb 2019
Towards Robust ResNet: A Small Step but A Giant Leap Jingfeng Zhang Bo Han L. Wynter K. H. Low Mohan Kankanhalli 24 41 0 28 Feb 2019
Fully Distributed Bayesian Optimization with Stochastic Policies Javier Garcia-Barcos Ruben Martinez-Cantin OffRL 22 14 0 26 Feb 2019
Topological Bayesian Optimization with Persistence Diagrams T. Shiraishi Tam Le H. Kashima M. Yamada 23 2 0 26 Feb 2019
Multiscale Gaussian Process Level Set Estimation S. Shekhar T. Javidi 37 17 0 26 Feb 2019
Bayesian optimisation under uncertain inputs Rafael Oliveira Lionel Ott F. Ramos 32 43 0 21 Feb 2019
Stable Bayesian Optimisation via Direct Stability Quantification A. Shilton Sunil R. Gupta Santu Rana Svetha Venkatesh Majid Abdolshah Dang Nguyen 11 0 0 21 Feb 2019
The Kalai-Smorodinski solution for many-objective Bayesian optimization M. Binois Victor Picheny P. Taillandier A. Habbal 26 17 0 18 Feb 2019
Procrastinating with Confidence: Near-Optimal, Anytime, Adaptive Algorithm Configuration Robert D. Kleinberg Kevin Leyton-Brown Brendan Lucier Devon R. Graham 17 20 0 14 Feb 2019
A Generalized Framework for Population Based Training Ang Li Ola Spyra Sagi Perel Valentin Dalibard Max Jaderberg Chenjie Gu David Budden Tim Harley Pramod Gupta 31 68 0 05 Feb 2019
Contextual Bandits with Continuous Actions: Smoothing, Zooming, and Adapting A. Krishnamurthy John Langford Aleksandrs Slivkins Chicheng Zhang OffRL 26 66 0 05 Feb 2019
On Local Optimizers of Acquisition Functions in Bayesian Optimization Jungtaek Kim Seungjin Choi 30 19 0 24 Jan 2019
Efficient surrogate modeling methods for large-scale Earth system models based on machine learning techniques D. Lu D. Ricciuto 22 43 0 16 Jan 2019
Data-efficient Auto-tuning with Bayesian Optimization: An Industrial Control Study Matthias Neumann-Brosig A. Marco D. Schwarzmann Sebastian Trimpe 24 91 0 15 Dec 2018
Efficient Model-Free Reinforcement Learning Using Gaussian Process Ying Fan Letian Chen Yizhou Wang GP 31 6 0 11 Dec 2018
Robust Super-Level Set Estimation using Gaussian Processes Andrea Zanette Junzi Zhang Mykel J. Kochenderfer 11 30 0 25 Nov 2018
Noisy Blackbox Optimization with Multi-Fidelity Queries: A Tree Search Approach Rajat Sen Kirthevasan Kandasamy Sanjay Shakkottai 14 23 0 24 Oct 2018
Automatic Configuration of Deep Neural Networks with EGO Bas van Stein Hao Wang Thomas Bäck 16 17 0 10 Oct 2018
Combining Bayesian Optimization and Lipschitz Optimization Mohamed Osama Ahmed Sharan Vaswani Mark Schmidt 36 22 0 10 Oct 2018
Learning to Optimize under Non-Stationarity Wang Chi Cheung D. Simchi-Levi Ruihao Zhu 47 133 0 06 Oct 2018
A Successive-Elimination Approach to Adaptive Robotic Sensing Esther Rolf David Fridovich-Keil Max Simchowitz Benjamin Recht Claire Tomlin 10 8 0 27 Sep 2018
Personalized Education at Scale S. Saarinen Evan Cater Michael Littman 9 1 0 24 Sep 2018
Bayesian functional optimisation with shape prior Pratibha Vellanki Santu Rana Sunil R. Gupta David Rubín de Celis Leal A. Sutti Murray Height Svetha Venkatesh 14 7 0 19 Sep 2018
Robustness Guarantees for Bayesian Inference with Gaussian Processes L. Cardelli Marta Kwiatkowska Luca Laurenti A. Patané AAML 24 52 0 17 Sep 2018
Learning-based attacks in cyber-physical systems M. J. Khojasteh Anatoly Khina M. Franceschetti T. Javidi AAML 13 12 0 17 Sep 2018
On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions Yusuke Tsuzuku Issei Sato AAML 24 62 0 11 Sep 2018
An informative path planning framework for UAV-based terrain monitoring Marija Popović Teresa Vidal-Calleja Gregory Hitz Jen Jen Chung Inkyu Sa Roland Siegwart Juan I. Nieto 19 136 0 08 Sep 2018