Convergence rates of efficient global optimization algorithms

18 January 2011

Papers citing "Convergence rates of efficient global optimization algorithms"

50 / 91 papers shown

Title
Wasserstein Barycenter Gaussian Process based Bayesian Optimization Antonio Candelieri Andrea Ponti Francesco Archetti 22 0 0 18 May 2025
Convergence Rates of Constrained Expected Improvement Haowei Wang Jingyi Wang Zhongxiang Dai Nai-Yuan Chiang Szu Hui Ng Cosmin G. Petra 27 0 0 16 May 2025
Bayesian Optimization by Kernel Regression and Density-based Exploration Tansheng Zhu Hongyu Zhou Ke Jin Xusheng Xu Qiufan Yuan Lijie Ji 248 0 0 10 Feb 2025
Improved Regret Analysis in Gaussian Process Bandits: Optimality for Noiseless Reward, RKHS norm, and Non-Stationary Variance S. Iwazaki Shion Takeno 85 1 0 10 Feb 2025
Every Call is Precious: Global Optimization of Black-Box Functions with Unknown Lipschitz Constants Fares Fourati Salma Kharrat Vaneet Aggarwal Mohamed-Slim Alouini 73 0 0 06 Feb 2025
Co-Learning Bayesian Optimization Zhendong Guo Yew-Soon Ong Tiantian He Haitao Liu 108 2 0 23 Jan 2025
Optimizing Posterior Samples for Bayesian Optimization via Rootfinding Taiwo A. Adebiyi Bach Do Ruda Zhang 114 2 0 29 Oct 2024
Lower Bounds for Time-Varying Kernelized Bandits Xu Cai Jonathan Scarlett 41 0 0 22 Oct 2024
Bayesian Optimization for Non-Convex Two-Stage Stochastic Optimization Problems Jack M. Buckingham Ivo Couckuyt Juergen Branke 51 0 0 30 Aug 2024
Global Optimisation of Black-Box Functions with Generative Models in the Wasserstein Space Tigran Ramazyan M. Hushchyn D. Derkach 41 0 0 16 Jul 2024
CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization Jacob O. Tørring Carl Hvarfner Luigi Nardi Magnus Sjalander 65 0 0 24 Jun 2024
Finding safe 3D robot grasps through efficient haptic exploration with unscented Bayesian optimization and collision penalty João Castanheira Pedro Vicente Ruben Martinez-Cantin L. Jamone Alexandre Bernardino 29 11 0 10 Feb 2024
On the development of a practical Bayesian optimisation algorithm for expensive experiments and simulations with changing environmental conditions Mike Diessner Kevin J. Wilson Richard D. Whalley 34 0 0 05 Feb 2024
Vanilla Bayesian Optimization Performs Great in High Dimensions Carl Hvarfner E. Hellsten Luigi Nardi 41 17 0 03 Feb 2024
A Unified Gaussian Process for Branching and Nested Hyperparameter Optimization Jiazhao Zhang Ying Hung Chung-Ching Lin Zicheng Liu 23 0 0 19 Jan 2024
LABCAT: Locally adaptive Bayesian optimization using principal-component-aligned trust regions E. Visser C. E. V. Daalen J. C. Schoeman 50 0 0 19 Nov 2023
Accelerating material discovery with a threshold-driven hybrid acquisition policy-based Bayesian optimization Ahmed Shoyeb Raihan H. Khosravi Srinjoy Das Imtiaz Ahmed 39 3 0 16 Nov 2023
Pseudo-Bayesian Optimization Haoxian Chen Henry Lam 37 2 0 15 Oct 2023
Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds Shion Takeno Yu Inatsu Masayuki Karasuyama 35 13 0 03 Feb 2023
Bayesian Optimization of 2D Echocardiography Segmentation Tung Tran Joshua V. Stough Xiaoyan Zhang C. Haggerty 26 3 0 17 Nov 2022
Global Optimization with Parametric Function Approximation Chong Liu Yu Wang 41 7 0 16 Nov 2022
Optimization on Manifolds via Graph Gaussian Processes Hwanwoo Kim D. Sanz-Alonso Ruiyi Yang 48 2 0 20 Oct 2022
Accelerating the Evolutionary Algorithms by Gaussian Process Regression with $ε$ -greedy acquisition function Rui Zhong En-zhan Zhang M. Munetomo 23 0 0 13 Oct 2022
Batch Bayesian optimisation via density-ratio estimation with guarantees Rafael Oliveira Louis C. Tiao Fabio Ramos 49 7 0 22 Sep 2022
Bayesian Optimization with Informative Covariance Afonso Eduardo Michael U. Gutmann 29 3 0 04 Aug 2022
Learning Skill-based Industrial Robot Tasks with User Priors Matthias Mayr Carl Hvarfner Konstantinos Chatzilygeroudis Luigi Nardi Volker Krueger 43 21 0 02 Aug 2022
Joint Entropy Search for Maximally-Informed Bayesian Optimization Carl Hvarfner Frank Hutter Luigi Nardi 46 36 0 09 Jun 2022
Relaxed Gaussian process interpolation: a goal-oriented approach to Bayesian optimization S. Petit Julien Bect E. Vázquez 51 1 0 07 Jun 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
High Dimensional Bayesian Optimization with Kernel Principal Component Analysis Kirill Antonov Elena Raponi Hao Wang Carola Doerr 27 10 0 28 Apr 2022
An Algebraically Converging Stochastic Gradient Descent Algorithm for Global Optimization Bjorn Engquist Kui Ren Yunan Yang 21 6 0 12 Apr 2022
Asymptotic Bounds for Smoothness Parameter Estimates in Gaussian Process Interpolation Toni Karvonen 32 1 0 10 Mar 2022
Bayesian Optimization Meets Hybrid Zero Dynamics: Safe Parameter Learning for Bipedal Locomotion Control Lizhi Yang Zhongyu Li Jun Zeng Koushil Sreenath 29 13 0 04 Mar 2022
Bayesian Optimization of Function Networks Raul Astudillo P. Frazier 32 36 0 31 Dec 2021
Triangulation candidates for Bayesian optimization R. Gramacy Anna Sauer Nathan Wycoff 34 13 0 14 Dec 2021
Towards Futuristic Autonomous Experimentation--A Surprise-Reacting Sequential Experiment Policy Imtiaz Ahmed Satish Bukkapatnam Bhaskar Botcha Yucheng Ding 43 5 0 01 Dec 2021
Non-smooth Bayesian Optimization in Tuning Problems Hengrui Luo J. Demmel Younghyun Cho Xin Li Yang Liu 25 13 0 15 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 39 51 0 20 Aug 2021
Counterfactual Explanations for Arbitrary Regression Models Thomas Spooner Danial Dervovic Jason Long Jon Shepard Jiahao Chen Daniele Magazzeni 24 26 0 29 Jun 2021
Lookahead Acquisition Functions for Finite-Horizon Time-Dependent Bayesian Optimization and Application to Quantum Optimal Control Sudharshan Ashwin Renganathan Jeffrey Larson Stefan M. Wild 23 7 0 20 May 2021
Bayesian Optimistic Optimisation with Exponentially Decaying Regret Hung The Tran Sunil R. Gupta Santu Rana Svetha Venkatesh 24 3 0 10 May 2021
One-parameter family of acquisition functions for efficient global optimization T. Kanazawa 35 2 0 26 Apr 2021
FixNorm: Dissecting Weight Decay for Training Deep Neural Networks Yucong Zhou Yunxiao Sun Zhaobai Zhong 29 6 0 29 Mar 2021
Small Sample Spaces for Gaussian Processes Toni Karvonen 24 13 0 04 Mar 2021
DEUP: Direct Epistemic Uncertainty Prediction Salem Lahlou Moksh Jain Hadi Nekoei V. Butoi Paul Bertin Jarrid Rector-Brooks Maksym Korablyov Yoshua Bengio PER UQLM UQCV UD 212 81 0 16 Feb 2021
Bayesian optimization with improved scalability and derivative information for efficient design of nanophotonic structures Xavier Garcia Santiago Sven Burger C. Rockstuhl Philipp‐Immanuel Schneider 20 12 0 08 Jan 2021
Asynchronous ε-Greedy Bayesian Optimisation George De Ath Richard Everson J. Fieldsend 35 5 0 15 Oct 2020
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning Sebastian Curi Felix Berkenkamp Andreas Krause 38 82 0 15 Jun 2020
Maximum likelihood estimation and uncertainty quantification for Gaussian process approximation of deterministic functions Toni Karvonen George Wynne Filip Tronarp Chris J. Oates Simo Särkkä 42 39 0 29 Jan 2020