Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization

4 April 2019

Papers citing "Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization"

22 / 22 papers shown

Title
Language-Based Bayesian Optimization Research Assistant (BORA) A. Cissé Xenophon Evangelopoulos V. Gusev Andrew I. Cooper 48 1 0 28 Jan 2025
OCCAM: Online Continuous Controller Adaptation with Meta-Learned Models Hersh Sanghvi Spencer Folk Camillo J Taylor 47 3 0 25 Jun 2024
Evolve Cost-aware Acquisition Functions Using Large Language Models Yiming Yao Fei Liu Ji Cheng Qingfu Zhang 51 7 0 25 Apr 2024
Solving Expensive Optimization Problems in Dynamic Environments with Meta-learning Huan Zhang Jinliang Ding Liang Feng Kay Chen Tan Ke Li 36 3 0 19 Oct 2023
RTDK-BO: High Dimensional Bayesian Optimization with Reinforced Transformer Deep kernels Alexander Shmakov Avisek Naug Vineet Gundecha Sahand Ghorbanpour Ricardo Luna Gutierrez Ashwin Ramesh Babu Antonio Guillen-Perez Soumyendu Sarkar 37 11 0 05 Oct 2023
When Deep Learning Meets Polyhedral Theory: A Survey Joey Huchette Gonzalo Muñoz Thiago Serra Calvin Tsay AI4CE 94 33 0 29 Apr 2023
Experience-Based Evolutionary Algorithms for Expensive Optimization Xunzhao Yu Yan Wang Ling Zhu Dimitar Filev Xin Yao 17 2 0 09 Apr 2023
MONGOOSE: Path-wise Smooth Bayesian Optimisation via Meta-learning Adam X. Yang Laurence Aitchison Henry B. Moss 29 4 0 22 Feb 2023
Transfer Learning for Bayesian Optimization: A Survey Tianyi Bai Yang Li Yu Shen Xinyi Zhang Wentao Zhang Bin Cui BDL 39 29 0 12 Feb 2023
AdaptSim: Task-Driven Simulation Adaptation for Sim-to-Real Transfer Allen Z. Ren Hongkai Dai Benjamin Burchfiel Anirudha Majumdar 27 14 0 09 Feb 2023
Speeding Up Multi-Objective Hyperparameter Optimization by Task Similarity-Based Meta-Learning for the Tree-Structured Parzen Estimator Shuhei Watanabe Noor H. Awad Masaki Onishi Frank Hutter 31 9 0 13 Dec 2022
PI is back! Switching Acquisition Functions in Bayesian Optimization C. Benjamins E. Raponi Anja Jankovic K. Blom Maria Laura Santoni Marius Lindauer Carola Doerr 38 5 0 02 Nov 2022
Recent Advances in Bayesian Optimization Xilu Wang Yaochu Jin Sebastian Schmitt Markus Olhofer 40 200 0 07 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 32 63 0 26 May 2022
OMLT: Optimization & Machine Learning Toolkit Francesco Ceccon Jordan Jalving Joshua Haddad Alexander Thebelt Calvin Tsay C. Laird Ruth Misener 34 70 0 04 Feb 2022
Improving Hyperparameter Optimization by Planning Ahead H. Jomaa Jonas K. Falkner Lars Schmidt-Thieme 22 0 0 15 Oct 2021
HPO-B: A Large-Scale Reproducible Benchmark for Black-Box HPO based on OpenML Sebastian Pineda Arango H. Jomaa Martin Wistuba Josif Grabocka 24 55 0 11 Jun 2021
JUMBO: Scalable Multi-task Bayesian Optimization using Offline Data Kourosh Hakhamaneshi Pieter Abbeel Vladimir M. Stojanović Aditya Grover 27 10 0 02 Jun 2021
Few-Shot Bayesian Optimization with Deep Kernel Surrogates Martin Wistuba Josif Grabocka BDL 42 68 0 19 Jan 2021
The Differentiable Cross-Entropy Method Brandon Amos Denis Yarats 29 54 0 27 Sep 2019
Meta-Surrogate Benchmarking for Hyperparameter Optimization Aaron Klein Zhenwen Dai Frank Hutter Neil D. Lawrence Javier I. González OffRL 6 36 0 30 May 2019
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 413 11,715 0 09 Mar 2017