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
Quality-Diversity Optimization: a novel branch of stochastic optimization Konstantinos Chatzilygeroudis Antoine Cully Vassilis Vassiliades Jean-Baptiste Mouret 65 91 0 08 Dec 2020
Distilled Thompson Sampling: Practical and Efficient Thompson Sampling via Imitation Learning Hongseok Namkoong Sam Daulton E. Bakshy OffRL 16 6 0 29 Nov 2020
Knowledge transfer across cell lines using Hybrid Gaussian Process models with entity embedding vectors Clemens Hutter M. Stosch M. N. C. Bournazou A. Butté 10 30 0 27 Nov 2020
Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning Chao Du Zhifeng Gao Shuo Yuan Lining Gao Z. Li Yifan Zeng Xiaoqiang Zhu Jian Xu Kun Gai Kuang-chih Lee 30 18 0 25 Nov 2020
All You Need is a Good Functional Prior for Bayesian Deep Learning Ba-Hien Tran Simone Rossi Dimitrios Milios Maurizio Filippone OOD BDL 31 56 0 25 Nov 2020
Model-based Reinforcement Learning for Continuous Control with Posterior Sampling Ying Fan Yifei Ming 33 17 0 20 Nov 2020
The Impact of Data on the Stability of Learning-Based Control- Extended Version Armin Lederer A. Capone Thomas Beckers Jonas Umlauft Sandra Hirche 14 10 0 20 Nov 2020
Value Function Approximations via Kernel Embeddings for No-Regret Reinforcement Learning Sayak Ray Chowdhury Rafael Oliveira OffRL 33 3 0 16 Nov 2020
Reward Biased Maximum Likelihood Estimation for Reinforcement Learning Akshay Mete Rahul Singh Xi Liu P. R. Kumar 18 24 0 16 Nov 2020
Asymptotically Optimal Information-Directed Sampling Johannes Kirschner Tor Lattimore Claire Vernade Csaba Szepesvári 25 33 0 11 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 44 18 0 09 Nov 2020
Pathwise Conditioning of Gaussian Processes James T. Wilson Viacheslav Borovitskiy Alexander Terenin P. Mostowsky M. Deisenroth 18 58 0 08 Nov 2020
Towards Fundamental Limits of Multi-armed Bandits with Random Walk Feedback Tianyu Wang Lin F. Yang Zizhuo Wang 11 0 0 03 Nov 2020
Learning in the Wild with Incremental Skeptical Gaussian Processes Andrea Bontempelli Stefano Teso Fausto Giunchiglia Andrea Passerini 14 20 0 02 Nov 2020
Gaussian Process Bandit Optimization of the Thermodynamic Variational Objective Vu-Linh Nguyen Vaden Masrani Rob Brekelmans Michael A. Osborne Frank Wood 29 5 0 29 Oct 2020
Gaussian Processes Model-based Control of Underactuated Balance Robots Kuo Chen J. Yi Dezhen Song 18 19 0 29 Oct 2020
A Domain-Shrinking based Bayesian Optimization Algorithm with Order-Optimal Regret Performance Sudeep Salgia Sattar Vakili Qing Zhao 48 33 0 27 Oct 2020
Federated Bayesian Optimization via Thompson Sampling Zhongxiang Dai K. H. Low Patrick Jaillet FedML 89 111 0 20 Oct 2020
Double-Linear Thompson Sampling for Context-Attentive Bandits Djallel Bouneffouf Raphael Feraud Sohini Upadhyay Y. Khazaeni Irina Rish 18 3 0 15 Oct 2020
Local Differential Privacy for Bayesian Optimization Xingyu Zhou Jian Tan 22 24 0 13 Oct 2020
Control Barrier Functions for Unknown Nonlinear Systems using Gaussian Processes Pushpak Jagtap George J. Pappas Majid Zamani 13 85 0 12 Oct 2020
Multi-Objective Bayesian Optimisation and Joint Inversion for Active Sensor Fusion S. Haan F. Ramos Dietmar Muller 4 4 0 12 Oct 2020
Learned Hardware/Software Co-Design of Neural Accelerators Zhan Shi Chirag Sakhuja Milad Hashemi Kevin Swersky Calvin Lin 19 15 0 05 Oct 2020
Parameter Optimization using high-dimensional Bayesian Optimization David Yenicelik 33 2 0 05 Oct 2020
Learning Set Functions that are Sparse in Non-Orthogonal Fourier Bases Chris Wendler Andisheh Amrollahi B. Seifert Andreas Krause Markus Püschel 30 9 0 01 Oct 2020
Mean-Variance Analysis in Bayesian Optimization under Uncertainty S. Iwazaki Yu Inatsu Ichiro Takeuchi 39 33 0 17 Sep 2020
Online learning-based trajectory tracking for underactuated vehicles with uncertain dynamics Thomas Beckers L. Colombo Sandra Hirche George J. Pappas 8 6 0 14 Sep 2020
Information-Theoretic Multi-Objective Bayesian Optimization with Continuous Approximations Syrine Belakaria Aryan Deshwal J. Doppa 36 7 0 12 Sep 2020
IEO: Intelligent Evolutionary Optimisation for Hyperparameter Tuning Yuxi Huan Fan Wu Michail Basios Leslie Kanthan Lingbo Li Baowen Xu VLM 19 4 0 10 Sep 2020
$Contraction $\mathcal{L}_1$-Adaptive Control using Gaussian Processes$ Contraction $\mathcal{L}_1$ -Adaptive Control using Gaussian Processes Aditya Gahlawat Arun Lakshmanan Lin Song Andrew Patterson Zhuohuan Wu N. Hovakimyan Evangelos Theodorou AI4CE 21 1 0 08 Sep 2020
Sequential Subspace Search for Functional Bayesian Optimization Incorporating Experimenter Intuition A. Shilton Sunil R. Gupta Santu Rana Svetha Venkatesh 14 3 0 08 Sep 2020
Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces Hung The Tran Sunil R. Gupta Santu Rana Huong Ha Svetha Venkatesh 37 6 0 05 Sep 2020
Max-value Entropy Search for Multi-Objective Bayesian Optimization with Constraints Syrine Belakaria Aryan Deshwal J. Doppa 35 131 0 01 Sep 2020
Safe Active Dynamics Learning and Control: A Sequential Exploration-Exploitation Framework T. Lew Apoorva Sharma James Harrison Andrew Bylard Marco Pavone 28 44 0 26 Aug 2020
Uncertainty aware Search Framework for Multi-Objective Bayesian Optimization with Constraints Syrine Belakaria Aryan Deshwal J. Doppa 18 6 0 16 Aug 2020
Kernel Methods for Cooperative Multi-Agent Contextual Bandits Abhimanyu Dubey Alex Pentland 12 29 0 14 Aug 2020
Multi-Agent Safe Planning with Gaussian Processes Zheqing Zhu Erdem Biyik Dorsa Sadigh 8 19 0 10 Aug 2020
Deterministic error bounds for kernel-based learning techniques under bounded noise E. Maddalena Paul Scharnhorst Colin N. Jones 33 45 0 10 Aug 2020
Learning-Based Safety-Stability-Driven Control for Safety-Critical Systems under Model Uncertainties Lei Zheng Jiesen Pan Ruicong Yang Hui Cheng Haifeng Hu 11 14 0 08 Aug 2020
IntelligentPooling: Practical Thompson Sampling for mHealth Sabina Tomkins Peng Liao P. Klasnja Susan Murphy 41 30 0 31 Jul 2020
Quantity vs. Quality: On Hyperparameter Optimization for Deep Reinforcement Learning L. Hertel Pierre Baldi D. Gillen BDL 31 12 0 29 Jul 2020
A Partially Observable MDP Approach for Sequential Testing for Infectious Diseases such as COVID-19 Rahul Singh Fang Liu Ness B. Shroff 18 6 0 25 Jul 2020
AttentionNAS: Spatiotemporal Attention Cell Search for Video Classification Xiaofang Wang Xuehan Xiong Maxim Neumann A. Piergiovanni Michael S. Ryoo A. Angelova Kris Kitani Wei Hua 24 51 0 23 Jul 2020
Filtered Poisson Process Bandit on a Continuum James A. Grant R. Szechtman 9 7 0 20 Jul 2020
PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning Alekh Agarwal Mikael Henaff Sham Kakade Wen Sun OffRL 24 109 0 16 Jul 2020
Forced-exploration free Strategies for Unimodal Bandits Hassan Saber Pierre Ménard Odalric-Ambrym Maillard 9 6 0 30 Jun 2020
MTAdam: Automatic Balancing of Multiple Training Loss Terms Itzik Malkiel Lior Wolf ODL 22 22 0 25 Jun 2020
Bayesian Optimization with a Prior for the Optimum Artur L. F. Souza Luigi Nardi Leonardo B. Oliveira K. Olukotun Marius Lindauer Frank Hutter 21 8 0 25 Jun 2020
Automatic Tuning of Stochastic Gradient Descent with Bayesian Optimisation Victor Picheny Vincent Dutordoir A. Artemev N. Durrande 19 2 0 25 Jun 2020
Green Machine Learning via Augmented Gaussian Processes and Multi-Information Source Optimization Antonio Candelieri R. Perego Francesco Archetti 19 16 0 25 Jun 2020