A Domain-Shrinking based Bayesian Optimization Algorithm with Order-Optimal Regret Performance

27 October 2020

Papers citing "A Domain-Shrinking based Bayesian Optimization Algorithm with Order-Optimal Regret Performance"

43 / 43 papers shown

Title
Improved Regret Analysis in Gaussian Process Bandits: Optimality for Noiseless Reward, RKHS norm, and Non-Stationary Variance S. Iwazaki Shion Takeno 111 2 0 10 Feb 2025
High-Dimensional Experimental Design and Kernel Bandits Romain Camilleri Julian Katz-Samuels Kevin Jamieson 47 56 0 12 May 2021
On Information Gain and Regret Bounds in Gaussian Process Bandits Sattar Vakili Kia Khezeli Victor Picheny GP 52 133 0 15 Sep 2020
On Lower Bounds for Standard and Robust Gaussian Process Bandit Optimization Xu Cai Jonathan Scarlett 72 30 0 20 Aug 2020
Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search Linnan Wang Rodrigo Fonseca Yuandong Tian 57 127 0 01 Jul 2020
Scalable Thompson Sampling using Sparse Gaussian Process Models Sattar Vakili Henry B. Moss A. Artemev Vincent Dutordoir Victor Picheny 40 35 0 09 Jun 2020
Multi-Scale Zero-Order Optimization of Smooth Functions in an RKHS S. Shekhar T. Javidi 29 20 0 11 May 2020
Stochastic Coordinate Minimization with Progressive Precision for Stochastic Convex Optimization Sudeep Salgia Qing Zhao Sattar Vakili 72 2 0 11 Mar 2020
Bandit optimisation of functions in the Matérn kernel RKHS David Janz David R. Burt Javier I. González 39 45 0 28 Jan 2020
Ordinal Bayesian Optimisation Victor Picheny Sattar Vakili A. Artemev 48 8 0 05 Dec 2019
Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret Daniele Calandriello Luigi Carratino A. Lazaric Michal Valko Lorenzo Rosasco GP 41 0 0 13 Mar 2019
Stochastic Gradient Descent on a Tree: an Adaptive and Robust Approach to Stochastic Convex Optimization Sattar Vakili Sudeep Salgia Qing Zhao 37 7 0 17 Jan 2019
Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior Zi Wang Beomjoon Kim L. Kaelbling 59 54 0 23 Nov 2018
Adversarially Robust Optimization with Gaussian Processes Ilija Bogunovic Jonathan Scarlett Stefanie Jegelka Volkan Cevher GP AAML 38 126 0 25 Oct 2018
Efficient Linear Bandits through Matrix Sketching Ilja Kuzborskij Leonardo Cella Nicolò Cesa-Bianchi 23 19 0 28 Sep 2018
Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences Motonobu Kanagawa Philipp Hennig Dino Sejdinovic Bharath K. Sriperumbudur GP BDL 126 342 0 06 Jul 2018
Scalable Gaussian Process Inference with Finite-data Mean and Variance Guarantees Jonathan H. Huggins Trevor Campbell Mikolaj Kasprzak Tamara Broderick 49 15 0 26 Jun 2018
Tight Regret Bounds for Bayesian Optimization in One Dimension Jonathan Scarlett 137 28 0 30 May 2018
Gaussian Process bandits with adaptive discretization S. Shekhar T. Javidi 56 52 0 05 Dec 2017
Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization Jonathan Scarlett Ilija Bogunovic Volkan Cevher 66 101 0 31 May 2017
On Kernelized Multi-armed Bandits Sayak Ray Chowdhury Aditya Gopalan 109 460 0 03 Apr 2017
Max-value Entropy Search for Efficient Bayesian Optimization Zi Wang Stefanie Jegelka 143 410 0 06 Mar 2017
Bayesian Optimization with Exponential Convergence Kenji Kawaguchi L. Kaelbling Tomás Lozano-Pérez 57 107 0 05 Apr 2016
Multi-fidelity Gaussian Process Bandit Optimisation Kirthevasan Kandasamy Gautam Dasarathy Junier B. Oliva J. Schneider Barnabás Póczós 51 77 0 20 Mar 2016
Stochastic Process Bandits: Upper Confidence Bounds Algorithms via Generic Chaining E. Contal Nicolas Vayatis 29 12 0 16 Feb 2016
High Dimensional Bayesian Optimisation and Bandits via Additive Models Kirthevasan Kandasamy J. Schneider Barnabás Póczós 53 355 0 05 Mar 2015
Theoretical Analysis of Bayesian Optimisation with Unknown Gaussian Process Hyper-Parameters Ziyun Wang Nando de Freitas 76 89 0 30 Jun 2014
An Information-Theoretic Analysis of Thompson Sampling Daniel Russo Benjamin Van Roy 153 425 0 21 Mar 2014
Bayesian Multi-Scale Optimistic Optimization Ziyun Wang B. Shakibi L. Jin Nando de Freitas 103 95 0 27 Feb 2014
Finite-Time Analysis of Kernelised Contextual Bandits Michal Valko N. Korda Rémi Munos I. Flaounas N. Cristianini 180 273 0 26 Sep 2013
Gaussian Processes for Big Data J. Hensman Nicolò Fusi Neil D. Lawrence GP 101 1,230 0 26 Sep 2013
Correlated random features for fast semi-supervised learning Brian McWilliams David Balduzzi J. M. Buhmann BDL 111 47 0 24 Jun 2013
Parallel Gaussian Process Optimization with Upper Confidence Bound and Pure Exploration E. Contal David Buffoni Alexandre Robicquet Nicolas Vayatis 58 213 0 19 Apr 2013
Learning to Optimize Via Posterior Sampling Daniel Russo Benjamin Van Roy 193 699 0 11 Jan 2013
Bayesian Optimization in a Billion Dimensions via Random Embeddings Ziyun Wang Frank Hutter M. Zoghi David Matheson Nando de Freitas 161 443 0 09 Jan 2013
Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations Nando de Freitas Alex Smola M. Zoghi 84 112 0 27 Jun 2012
Parallelizing Exploration-Exploitation Tradeoffs with Gaussian Process Bandit Optimization Thomas Desautels Andreas Krause J. W. Burdick 101 473 0 27 Jun 2012
Hybrid Batch Bayesian Optimization J. Azimi A. Jalali Xiaoli Z. Fern 72 70 0 25 Feb 2012
Convergence rates of efficient global optimization algorithms Adam D. Bull 114 641 0 18 Jan 2011
Portfolio Allocation for Bayesian Optimization E. Brochu Matthew W. Hoffman Nando de Freitas 387 280 0 28 Sep 2010
X-Armed Bandits Sébastien Bubeck Rémi Munos Gilles Stoltz Csaba Szepesvari 152 383 0 25 Jan 2010
Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design Niranjan Srinivas Andreas Krause Sham Kakade Matthias Seeger 146 1,619 0 21 Dec 2009
Multi-Armed Bandits in Metric Spaces Robert D. Kleinberg Aleksandrs Slivkins E. Upfal 395 468 0 29 Sep 2008