Warm Starting Bayesian Optimization

11 August 2016

Papers citing "Warm Starting Bayesian Optimization"

31 / 31 papers shown

Title
Why risk matters for protein binder design Tudor-Stefan Cotet Igor Krawczuk 114 0 0 31 Mar 2025
Language-Based Bayesian Optimization Research Assistant (BORA) A. Cissé Xenophon Evangelopoulos V. Gusev Andrew I. Cooper 139 1 0 28 Jan 2025
Sequential Large Language Model-Based Hyper-parameter Optimization Kanan Mahammadli Seyda Ertekin 238 5 0 27 Oct 2024
Robust Transfer Learning for Active Level Set Estimation with Locally Adaptive Gaussian Process Prior Giang Ngo Dang Nguyen Sunil Gupta 54 0 0 08 Oct 2024
Improving Hyperparameter Optimization with Checkpointed Model Weights Nikhil Mehta Jonathan Lorraine Steve Masson Ramanathan Arunachalam Zaid Pervaiz Bhat James Lucas Arun George Zachariah 107 4 0 26 Jun 2024
Reinforced In-Context Black-Box Optimization Lei Song Chenxiao Gao Ke Xue Chenyang Wu Dong Li Haifeng Zhang Zongzhang Zhang Chao Qian 104 4 0 27 Feb 2024
Large Language Models to Enhance Bayesian Optimization Tennison Liu Nicolás Astorga Nabeel Seedat M. Schaar 156 59 0 06 Feb 2024
Transfer Learning for Bayesian Optimization: A Survey Tianyi Bai Yang Li Yu Shen Xinyi Zhang Wentao Zhang Tengjiao Wang BDL 78 31 0 12 Feb 2023
Pre-training helps Bayesian optimization too Zehao Wang George E. Dahl Kevin Swersky Chansoo Lee Zelda E. Mariet Zachary Nado Justin Gilmer Jasper Snoek Zoubin Ghahramani 70 9 0 07 Jul 2022
On Provably Robust Meta-Bayesian Optimization Zhongxiang Dai Yizhou Chen Haibin Yu K. H. Low Patrick Jaillet AAML 65 10 0 14 Jun 2022
Towards Learning Universal Hyperparameter Optimizers with Transformers Yutian Chen Xingyou Song Chansoo Lee Zehao Wang Qiuyi Zhang ... Greg Kochanski Arnaud Doucet MarcÁurelio Ranzato Sagi Perel Nando de Freitas 105 65 0 26 May 2022
Pre-trained Gaussian processes for Bayesian optimization Zehao Wang George E. Dahl Kevin Swersky Chansoo Lee Zachary Nado Justin Gilmer Jasper Snoek Zoubin Ghahramani 151 46 0 16 Sep 2021
Amortized Auto-Tuning: Cost-Efficient Bayesian Transfer Optimization for Hyperparameter Recommendation Yuxin Xiao Eric P. Xing Willie Neiswanger 95 5 0 17 Jun 2021
JUMBO: Scalable Multi-task Bayesian Optimization using Offline Data Kourosh Hakhamaneshi Pieter Abbeel Vladimir M. Stojanović Aditya Grover 74 10 0 02 Jun 2021
Warm Starting CMA-ES for Hyperparameter Optimization Masahiro Nomura Shuhei Watanabe Youhei Akimoto Yoshihiko Ozaki Masaki Onishi 93 43 0 13 Dec 2020
Scalable Bayesian Optimization with Sparse Gaussian Process Models Ang Yang 50 0 0 26 Oct 2020
Automatic Tuning of Stochastic Gradient Descent with Bayesian Optimisation Victor Picheny Vincent Dutordoir A. Artemev N. Durrande 50 2 0 25 Jun 2020
Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels Binxin Ru Xingchen Wan Xiaowen Dong Michael A. Osborne 86 22 0 13 Jun 2020
Neural Architecture Generator Optimization Binxin Ru P. Esperança Fabio Maria Carlucci 86 40 0 03 Apr 2020
On Hyper-parameter Tuning for Stochastic Optimization Algorithms Haotian Zhang Jianyong Sun Zongben Xu 58 0 0 04 Mar 2020
Incorporating Expert Prior Knowledge into Experimental Design via Posterior Sampling Cheng Li Sunil R. Gupta Santu Rana Vu Nguyen A. Robles-Kelly Svetha Venkatesh 104 15 0 26 Feb 2020
Practical Bayesian Optimization of Objectives with Conditioning Variables Michael Pearce Janis Klaise Matthew J. Groves 70 1 0 23 Feb 2020
A Quantile-based Approach for Hyperparameter Transfer Learning David Salinas Huibin Shen Valerio Perrone 52 3 0 30 Sep 2019
Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning Valerio Perrone Huibin Shen Matthias Seeger Cédric Archambeau Rodolphe Jenatton 75 97 0 27 Sep 2019
Efficient Transfer Bayesian Optimization with Auxiliary Information Tomoharu Iwata Takuma Otsuka 69 2 0 17 Sep 2019
Bayesian Optimization for Policy Search via Online-Offline Experimentation Benjamin Letham E. Bakshy OffRL 97 56 0 01 Apr 2019
Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior Zi Wang Beomjoon Kim L. Kaelbling 77 54 0 23 Nov 2018
Hyperparameter Learning via Distributional Transfer H. Law P. Zhao Lucian Chan Junzhou Huang Dino Sejdinovic 85 25 0 15 Oct 2018
BOHB: Robust and Efficient Hyperparameter Optimization at Scale Stefan Falkner Aaron Klein Frank Hutter BDL 242 1,102 0 04 Jul 2018
Practical Transfer Learning for Bayesian Optimization Matthias Feurer Benjamin Letham Frank Hutter E. Bakshy 142 35 0 06 Feb 2018
Multi-Information Source Optimization Matthias Poloczek Jialei Wang P. Frazier 104 198 0 01 Mar 2016