Multi-Information Source Optimization

1 March 2016

Papers citing "Multi-Information Source Optimization"

50 / 103 papers shown

Title
Interim Report on Human-Guided Adaptive Hyperparameter Optimization with Multi-Fidelity Sprints Michael Kamfonas 16 0 0 14 May 2025
Data Mixture Optimization: A Multi-fidelity Multi-scale Bayesian Framework Thomson Yen Andrew Siah Haozhe Chen Tianyi Peng Daniel Guetta Hongseok Namkoong 48 0 0 26 Mar 2025
Bayesian Optimization for Unknown Cost-Varying Variable Subsets with No-Regret Costs Vu Viet Hoang Quoc Anh Hoang Nguyen Hung Tran The 79 0 0 20 Dec 2024
Rate-Informed Discovery via Bayesian Adaptive Multifidelity Sampling Aman Sinha Payam Nikdel Supratik Paul Shimon Whiteson 76 0 0 26 Nov 2024
Multifidelity Cross-validation Sudharshan Ashwin Renganathan Kade Carlson 33 0 0 01 Jul 2024
Improving Hyperparameter Optimization with Checkpointed Model Weights Nikhil Mehta Jonathan Lorraine Steve Masson Ramanathan Arunachalam Zaid Pervaiz Bhat James Lucas Arun George Zachariah 49 4 0 26 Jun 2024
Active learning for affinity prediction of antibodies Alexandra Gessner Sebastian W. Ober Owen Vickery Dino Oglic Talip Uçar AI4CE 26 4 0 11 Jun 2024
Optimal Multi-Fidelity Best-Arm Identification Riccardo Poiani Rémy Degenne Emilie Kaufmann Alberto Maria Metelli Marcello Restelli 16 1 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 35 3 0 29 May 2024
Cost-Sensitive Multi-Fidelity Bayesian Optimization with Transfer of Learning Curve Extrapolation Dong Bok Lee Aoxuan Silvia Zhang Byung-Hoon Kim Junhyeon Park Juho Lee Sung Ju Hwang Haebeom Lee 34 1 0 28 May 2024
CAGES: Cost-Aware Gradient Entropy Search for Efficient Local Multi-Fidelity Bayesian Optimization Wei-Ting Tang J. Paulson 15 1 0 13 May 2024
Multi-Fidelity Bayesian Optimization With Across-Task Transferable Max-Value Entropy Search Yunchuan Zhang Sangwoo Park Osvaldo Simeone 45 5 0 14 Mar 2024
Multifidelity linear regression for scientific machine learning from scarce data Elizabeth Qian Dayoung Kang Vignesh Sella Anirban Chaudhuri AI4CE 81 1 0 13 Mar 2024
Global Safe Sequential Learning via Efficient Knowledge Transfer Cen-You Li Olaf Duennbier Marc Toussaint Barbara Rakitsch Christoph Zimmer 52 2 0 22 Feb 2024
FlexHB: a More Efficient and Flexible Framework for Hyperparameter Optimization Yang Zhang Haiyang Wu Yuekui Yang 43 0 0 21 Feb 2024
Multi-Fidelity Methods for Optimization: A Survey Ke Li Fan Li AI4CE 35 6 0 15 Feb 2024
Combining additivity and active subspaces for high-dimensional Gaussian process modeling M. Binois Victor Picheny 28 0 0 06 Feb 2024
Long-run Behaviour of Multi-fidelity Bayesian Optimisation G. Dovonon Jakob Zeitler 29 1 0 19 Dec 2023
Scalable Meta-Learning with Gaussian Processes Petru Tighineanu Lukas Großberger P. Baireuther Kathrin Skubch Stefan Falkner Julia Vinogradska Felix Berkenkamp 26 4 0 01 Dec 2023
A Bayesian approach for prompt optimization in pre-trained language models Antonio Sabbatella Andrea Ponti Antonio Candelieri I. Giordani F. Archetti 31 1 0 01 Dec 2023
Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed Spaces Leonard Papenmeier Luigi Nardi Matthias Poloczek 32 12 0 02 Jul 2023
Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems Truong X. Nghiem Ján Drgoňa Colin N. Jones Zoltán Nagy Roland Schwan ... J. Paulson Andrea Carron M. Zeilinger Wenceslao Shaw-Cortez D. Vrabie PINN AI4CE 34 30 0 24 Jun 2023
Differentiable Multi-Fidelity Fusion: Efficient Learning of Physics Simulations with Neural Architecture Search and Transfer Learning Yuwen Deng Wang Kang Wei W. Xing OOD AI4CE 34 0 0 12 Jun 2023
Hyper-parameter Tuning for Adversarially Robust Models Pedro Mendes Paolo Romano David Garlan AAML 19 2 0 05 Apr 2023
Scalable Bayesian optimization with high-dimensional outputs using randomized prior networks Mohamed Aziz Bhouri M. Joly Robert Yu S. Sarkar P. Perdikaris BDL UQCV AI4CE 19 1 0 14 Feb 2023
Multi-Fidelity Covariance Estimation in the Log-Euclidean Geometry A. Maurais Terrence Alsup Benjamin Peherstorfer Youssef Marzouk 25 7 0 31 Jan 2023
GAR: Generalized Autoregression for Multi-Fidelity Fusion Yuxin Wang Zhengrong Xing Wei W. Xing AI4CE 14 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 37 8 0 17 Dec 2022
Multi-Fidelity Bayesian Optimization with Unreliable Information Sources P. Mikkola Julien Martinelli Louis Filstroff Samuel Kaski 30 10 0 25 Oct 2022
Efficient computation of the Knowledge Gradient for Bayesian Optimization Juan Ungredda Michael Pearce Juergen Branke 35 2 0 30 Sep 2022
Non-Myopic Multifidelity Bayesian Optimization Francesco Di Fiore L. Mainini 11 3 0 13 Jul 2022
Pre-training helps Bayesian optimization too Z. Wang George E. Dahl Kevin Swersky Chansoo Lee Zelda E. Mariet Zachary Nado Justin Gilmer Jasper Snoek Zoubin Ghahramani 20 9 0 07 Jul 2022
On Provably Robust Meta-Bayesian Optimization Zhongxiang Dai Yizhou Chen Haibin Yu K. H. Low P. Jaillet AAML 20 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 Bin Cui 33 15 0 06 Jun 2022
Towards Learning Universal Hyperparameter Optimizers with Transformers Yutian Chen Xingyou Song Chansoo Lee Z. Wang Qiuyi Zhang ... Greg Kochanski Arnaud Doucet MarcÁurelio Ranzato Sagi Perel Nando de Freitas 26 63 0 26 May 2022
Fair and Green Hyperparameter Optimization via Multi-objective and Multiple Information Source Bayesian Optimization Antonio Candelieri Andrea Ponti F. Archetti 27 15 0 18 May 2022
Meta-learning Adaptive Deep Kernel Gaussian Processes for Molecular Property Prediction Wenlin Chen Austin Tripp José Miguel Hernández-Lobato 16 23 0 05 May 2022
Supervising the Multi-Fidelity Race of Hyperparameter Configurations Martin Wistuba Arlind Kadra Josif Grabocka 20 14 0 20 Feb 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 27 19 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 Bin Cui 30 26 0 18 Jan 2022
Thinking inside the box: A tutorial on grey-box Bayesian optimization Raul Astudillo P. Frazier 20 35 0 02 Jan 2022
Transfer Learning with Gaussian Processes for Bayesian Optimization Petru Tighineanu Kathrin Skubch P. Baireuther Attila Reiss Felix Berkenkamp Julia Vinogradska 14 32 0 22 Nov 2021
Multi-Step Budgeted Bayesian Optimization with Unknown Evaluation Costs Raul Astudillo Daniel R. Jiang Maximilian Balandat E. Bakshy P. Frazier 8 18 0 12 Nov 2021
LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso Kenan Sehic Alexandre Gramfort Joseph Salmon Luigi Nardi 22 35 0 04 Nov 2021
Pre-trained Gaussian processes for Bayesian optimization Z. Wang George E. Dahl Kevin Swersky Chansoo Lee Zachary Nado Justin Gilmer Jasper Snoek Zoubin Ghahramani 55 40 0 16 Sep 2021
HyperJump: Accelerating HyperBand via Risk Modelling Pedro Mendes Maria Casimiro Paolo Romano David Garlan 22 7 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 Bin Cui LRM 29 44 0 19 Jul 2021
Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks Shibo Li Robert M. Kirby Shandian Zhe 16 13 0 18 Jun 2021
Nonmyopic Multifidelity Active Search Quan Nguyen Arghavan Modiri Roman Garnett 13 1 0 11 Jun 2021
A Nonmyopic Approach to Cost-Constrained Bayesian Optimization E. Lee David Eriksson Valerio Perrone Matthias Seeger 33 22 0 10 Jun 2021