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Multi-Information Source Optimization

1 March 2016

Papers citing "Multi-Information Source Optimization"

50 / 68 papers shown

Title
Interim Report on Human-Guided Adaptive Hyperparameter Optimization with Multi-Fidelity Sprints Michael Kamfonas 71 0 0 14 May 2025
Optimal Multi-Fidelity Best-Arm Identification Riccardo Poiani Rémy Degenne Emilie Kaufmann Alberto Maria Metelli Marcello Restelli 179 2 0 05 Jun 2024
Efficient Black-box Adversarial Attacks via Bayesian Optimization Guided by a Function Prior Shuyu Cheng Yibo Miao Yinpeng Dong Xiao Yang Xiao-Shan Gao Jun Zhu AAML 104 5 0 29 May 2024
CAGES: Cost-Aware Gradient Entropy Search for Efficient Local Multi-Fidelity Bayesian Optimization Wei-Ting Tang J. Paulson 77 1 0 13 May 2024
Multi-Fidelity Bayesian Optimization With Across-Task Transferable Max-Value Entropy Search Yunchuan Zhang Sangwoo Park Osvaldo Simeone 105 5 0 14 Mar 2024
Global Safe Sequential Learning via Efficient Knowledge Transfer Cen-You Li Olaf Duennbier Marc Toussaint Barbara Rakitsch Christoph Zimmer 130 2 0 22 Feb 2024
Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed Spaces Leonard Papenmeier Luigi Nardi Matthias Poloczek 128 13 0 02 Jul 2023
Multi-Fidelity Covariance Estimation in the Log-Euclidean Geometry A. Maurais Terrence Alsup Benjamin Peherstorfer Youssef Marzouk 102 7 0 31 Jan 2023
GAR: Generalized Autoregression for Multi-Fidelity Fusion Yuxin Wang Zhengrong Xing Wei W. Xing AI4CE 56 3 0 13 Jan 2023
On Noisy Evaluation in Federated Hyperparameter Tuning Kevin Kuo Pratiksha Thaker M. Khodak John Nguyen Daniel Jiang Ameet Talwalkar Virginia Smith FedML 123 8 0 17 Dec 2022
Multi-Fidelity Bayesian Optimization with Unreliable Information Sources P. Mikkola Julien Martinelli Louis Filstroff Samuel Kaski 108 11 0 25 Oct 2022
Non-Myopic Multifidelity Bayesian Optimization Francesco Di Fiore L. Mainini 106 3 0 13 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
TransBO: Hyperparameter Optimization via Two-Phase Transfer Learning Yang Li Yu Shen Huaijun Jiang Wentao Zhang Zhi-Xin Yang Ce Zhang Tengjiao Wang 76 15 0 06 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
Fair and Green Hyperparameter Optimization via Multi-objective and Multiple Information Source Bayesian Optimization Antonio Candelieri Andrea Ponti Francesco Archetti 63 18 0 18 May 2022
Meta-learning Adaptive Deep Kernel Gaussian Processes for Molecular Property Prediction Jiajun He Austin Tripp José Miguel Hernández-Lobato 66 23 0 05 May 2022
SnAKe: Bayesian Optimization with Pathwise Exploration Jose Pablo Folch Shiqiang Zhang Robert M. Lee B. Shafei David Walz Calvin Tsay Mark van der Wilk Ruth Misener 88 20 0 31 Jan 2022
Hyper-Tune: Towards Efficient Hyper-parameter Tuning at Scale Yang Li Yu Shen Huaijun Jiang Wentao Zhang Jixiang Li Ji Liu Ce Zhang Tengjiao Wang 64 26 0 18 Jan 2022
Thinking inside the box: A tutorial on grey-box Bayesian optimization Raul Astudillo P. Frazier 102 36 0 02 Jan 2022
Transfer Learning with Gaussian Processes for Bayesian Optimization Petru Tighineanu Kathrin Skubch P. Baireuther Attila Reiss Felix Berkenkamp Julia Vinogradska 62 33 0 22 Nov 2021
LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso Kenan Sehic Alexandre Gramfort Joseph Salmon Luigi Nardi 116 39 0 04 Nov 2021
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
HyperJump: Accelerating HyperBand via Risk Modelling Pedro Mendes Maria Casimiro Paolo Romano David Garlan 73 8 0 05 Aug 2021
VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition Yang Li Yu Shen Wentao Zhang Jiawei Jiang Bolin Ding ... Jingren Zhou Zhi-Xin Yang Wentao Wu Ce Zhang Tengjiao Wang LRM 61 46 0 19 Jul 2021
Nonmyopic Multifidelity Active Search Quan Nguyen Arghavan Modiri Roman Garnett 127 1 0 11 Jun 2021
A Nonmyopic Approach to Cost-Constrained Bayesian Optimization E. Lee David Eriksson Valerio Perrone Matthias Seeger 88 23 0 10 Jun 2021
OpenBox: A Generalized Black-box Optimization Service Yang Li Yu Shen Wentao Zhang Yuan-Wei Chen Huaijun Jiang ... Jinyang Gao Wentao Wu Zhi-Xin Yang Ce Zhang Tengjiao Wang 81 77 0 01 Jun 2021
Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020 Ryan Turner David Eriksson M. McCourt J. Kiili Eero Laaksonen Zhen Xu Isabelle M Guyon BDL 102 304 0 20 Apr 2021
Problem-fluent models for complex decision-making in autonomous materials research Soojung Baek Kristofer G. Reyes AI4CE 48 2 0 13 Mar 2021
Warm Starting CMA-ES for Hyperparameter Optimization Masahiro Nomura Shuhei Watanabe Youhei Akimoto Yoshihiko Ozaki Masaki Onishi 95 43 0 13 Dec 2020
Efficient Automatic CASH via Rising Bandits Yang Li Jiawei Jiang Jinyang Gao Yingxia Shao Ce Zhang Tengjiao Wang 83 34 0 08 Dec 2020
MFES-HB: Efficient Hyperband with Multi-Fidelity Quality Measurements Yang Li Yu Shen Jiawei Jiang Jinyang Gao Ce Zhang Tengjiao Wang 71 28 0 05 Dec 2020
Deep Multi-Fidelity Active Learning of High-dimensional Outputs Shibo Li Robert M. Kirby Shandian Zhe AI4CE 57 28 0 02 Dec 2020
Federated Bayesian Optimization via Thompson Sampling Zhongxiang Dai K. H. Low Patrick Jaillet FedML 145 113 0 20 Oct 2020
Quantity vs. Quality: On Hyperparameter Optimization for Deep Reinforcement Learning L. Hertel Pierre Baldi D. Gillen BDL 75 13 0 29 Jul 2020
Sequential design of multi-fidelity computer experiments: maximizing the rate of stepwise uncertainty reduction Rémi Stroh Julien Bect S. Demeyer N. Fischer Damien Marquis E. Vázquez 40 13 0 27 Jul 2020
Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning Matthias Feurer Katharina Eggensperger Stefan Falkner Marius Lindauer Frank Hutter 140 285 0 08 Jul 2020
Learning excursion sets of vector-valued Gaussian random fields for autonomous ocean sampling T. Fossum Cédric Travelletti J. Eidsvik D. Ginsbourger K. Rajan 36 18 0 07 Jul 2020
Multi-Fidelity Bayesian Optimization via Deep Neural Networks Shibo Li Wei W. Xing Mike Kirby Shandian Zhe 75 54 0 06 Jul 2020
BOSH: Bayesian Optimization by Sampling Hierarchically Henry B. Moss David S. Leslie Paul Rayson 66 8 0 02 Jul 2020
Green Machine Learning via Augmented Gaussian Processes and Multi-Information Source Optimization Antonio Candelieri R. Perego Francesco Archetti 47 19 0 25 Jun 2020
MUMBO: MUlti-task Max-value Bayesian Optimization Henry B. Moss David S. Leslie Paul Rayson 88 34 0 22 Jun 2020
Model-based Asynchronous Hyperparameter and Neural Architecture Search Aaron Klein Louis C. Tiao Thibaut Lienart Cédric Archambeau Matthias Seeger 62 5 0 24 Mar 2020
Cost-aware Bayesian Optimization E. Lee Valerio Perrone Cédric Archambeau Matthias Seeger 157 58 0 22 Mar 2020
Why Non-myopic Bayesian Optimization is Promising and How Far Should We Look-ahead? A Study via Rollout Xubo Yue Raed Al Kontar 104 38 0 04 Nov 2019
Dynamic Subgoal-based Exploration via Bayesian Optimization Yijia Wang Matthias Poloczek Daniel R. Jiang 91 3 0 21 Oct 2019
BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization Maximilian Balandat Brian Karrer Daniel R. Jiang Sam Daulton Benjamin Letham A. Wilson E. Bakshy 75 93 0 14 Oct 2019
Active learning for level set estimation under cost-dependent input uncertainty Yu Inatsu Masayuki Karasuyama Keiichi Inoue Ichiro Takeuchi 42 5 0 13 Sep 2019
Bayesian Optimization with Binary Auxiliary Information Yehong Zhang Zhongxiang Dai K. H. Low 64 26 0 17 Jun 2019