Active Learning of Linear Embeddings for Gaussian Processes

24 October 2013

Papers citing "Active Learning of Linear Embeddings for Gaussian Processes"

44 / 44 papers shown

Title
Towards Universal Offline Black-Box Optimization via Learning Language Model Embeddings Rong-Xi Tan Ming Chen Ke Xue Yao Wang Yaoyuan Wang Sheng Fu Chao Qian OffRL 32 0 0 08 Jun 2025
Posterior Inference with Diffusion Models for High-dimensional Black-box Optimization Taeyoung Yun Kiyoung Om Jaewoo Lee Sujin Yun Jinkyoo Park 119 2 0 24 Feb 2025
Amortized Active Learning for Nonparametric Functions Cen-You Li Marc Toussaint Barbara Rakitsch Christoph Zimmer 55 0 0 25 Jul 2024
Global Optimisation of Black-Box Functions with Generative Models in the Wasserstein Space Tigran Ramazyan M. Hushchyn D. Derkach 69 0 0 16 Jul 2024
A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences Miguel González Duque Richard Michael Simon Bartels Yevgen Zainchkovskyy Søren Hauberg Wouter Boomsma 74 5 0 07 Jun 2024
Latent Energy-Based Odyssey: Black-Box Optimization via Expanded Exploration in the Energy-Based Latent Space Peiyu Yu Dinghuai Zhang Hengzhi He Xiaojian Ma Ruiyao Miao ... Deqian Kong Ruiqi Gao Jianwen Xie Guang Cheng Ying Nian Wu 103 6 0 27 May 2024
Combining additivity and active subspaces for high-dimensional Gaussian process modeling M. Binois Victor Picheny 92 0 0 06 Feb 2024
High-dimensional Bayesian Optimization via Covariance Matrix Adaptation Strategy Lam Ngo Huong Ha Jeffrey Chan Vu-Linh Nguyen Hongyu Zhang 85 2 0 05 Feb 2024
Vanilla Bayesian Optimization Performs Great in High Dimensions Carl Hvarfner E. Hellsten Luigi Nardi 99 28 0 03 Feb 2024
High-dimensional mixed-categorical Gaussian processes with application to multidisciplinary design optimization for a green aircraft P. Saves Y. Diouane N. Bartoli T. Lefebvre J. Morlier 99 5 0 10 Nov 2023
SMT 2.0: A Surrogate Modeling Toolbox with a focus on Hierarchical and Mixed Variables Gaussian Processes P. Saves R. Lafage N. Bartoli Y. Diouane J. Bussemaker T. Lefebvre John T. Hwang J. Morlier J. Martins MoE 112 72 0 23 May 2023
Active Cost-aware Labeling of Streaming Data Ti-jian Cai Kirthevasan Kandasamy 51 3 0 13 Apr 2023
Hierarchical-Hyperplane Kernels for Actively Learning Gaussian Process Models of Nonstationary Systems M. Bitzer Mona Meister Christoph Zimmer 77 6 0 17 Mar 2023
Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-based Embeddings Aryan Deshwal Sebastian Ament Maximilian Balandat E. Bakshy J. Doppa David Eriksson 143 23 0 03 Mar 2023
Linear Embedding-based High-dimensional Batch Bayesian Optimization without Reconstruction Mappings Shuhei A Horiguchi Tomoharu Iwata Taku Tsuzuki Yosuke Ozawa 40 1 0 02 Nov 2022
Bayesian Optimization with Informative Covariance Afonso Eduardo Michael U. Gutmann 77 3 0 04 Aug 2022
Safe Active Learning for Multi-Output Gaussian Processes Cen-You Li Barbara Rakitsch Christoph Zimmer UQCV 136 18 0 28 Mar 2022
Local Latent Space Bayesian Optimization over Structured Inputs Natalie Maus Haydn Thomas Jones Juston Moore Matt J. Kusner John Bradshaw Jacob R. Gardner BDL 120 72 0 28 Jan 2022
LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso Kenan Sehic Alexandre Gramfort Joseph Salmon Luigi Nardi 116 39 0 04 Nov 2021
Global optimization using random embeddings C. Cartis E. Massart Adilet Otemissov 66 9 0 26 Jul 2021
High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning Antoine Grosnit Rasul Tutunov A. Maraval Ryan-Rhys Griffiths Alexander I. Cowen-Rivers ... Wenlong Lyu Zhitang Chen Jun Wang Jan Peters Haitham Bou-Ammar BDL DRL 101 61 0 07 Jun 2021
High-Dimensional Bayesian Optimization with Sparse Axis-Aligned Subspaces David Eriksson M. Jankowiak 113 148 0 27 Feb 2021
Sensitivity Prewarping for Local Surrogate Modeling Nathan Wycoff M. Binois R. Gramacy 75 10 0 15 Jan 2021
Good practices for Bayesian Optimization of high dimensional structured spaces E. Siivola Javier I. González Andrei Paleyes Aki Vehtari 95 38 0 31 Dec 2020
High-Dimensional Bayesian Optimization via Nested Riemannian Manifolds Noémie Jaquier Leonel Rozo 103 24 0 21 Oct 2020
Parameter Optimization using high-dimensional Bayesian Optimization David Yenicelik 72 2 0 05 Oct 2020
Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces Hung The Tran Sunil R. Gupta Santu Rana Huong Ha Svetha Venkatesh 78 7 0 05 Sep 2020
Bayesian learning of orthogonal embeddings for multi-fidelity Gaussian Processes Panagiotis Tsilifis Piyush Pandita Sayan Ghosh Valeria Andreoli T. Vandeputte Liping Wang 42 19 0 05 Aug 2020
Sample-Efficient Optimization in the Latent Space of Deep Generative Models via Weighted Retraining Austin Tripp Erik A. Daxberger José Miguel Hernández-Lobato MedIm 110 143 0 16 Jun 2020
Does Unsupervised Architecture Representation Learning Help Neural Architecture Search? Shen Yan Yu Zheng Wei Ao Xiao Zeng Mi Zhang SSL AI4CE 112 104 0 12 Jun 2020
ENTMOOT: A Framework for Optimization over Ensemble Tree Models Alexander Thebelt Jan Kronqvist Miten Mistry Robert M. Lee Nathan Sudermann-Merx Ruth Misener 89 57 0 10 Mar 2020
Black-Box Optimization with Local Generative Surrogates S. Shirobokov V. Belavin Michael Kagan Andrey Ustyuzhanin A. G. Baydin 51 3 0 11 Feb 2020
Accelerating Psychometric Screening Tests With Bayesian Active Differential Selection Trevor J. Larsen Gustavo Malkomes D. Barbour 16 4 0 04 Feb 2020
Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization Benjamin Letham Roberto Calandra Akshara Rai E. Bakshy 122 116 0 31 Jan 2020
Bayesian Optimization for Policy Search in High-Dimensional Systems via Automatic Domain Selection Lukas P. Frohlich Edgar D. Klenske Christian Daniel Melanie Zeilinger 99 12 0 21 Jan 2020
Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization Hung The Tran Sunil R. Gupta Santu Rana Svetha Venkatesh 65 14 0 27 Nov 2019
Deep Kernels with Probabilistic Embeddings for Small-Data Learning Ankur Mallick Chaitanya Dwivedi B. Kailkhura Gauri Joshi T. Y. Han BDL UQCV 53 8 0 13 Oct 2019
Evolving Gaussian Process kernels from elementary mathematical expressions Ibai Roman Roberto Santana A. Mendiburu Jose A. Lozano 44 3 0 11 Oct 2019
Scalable Global Optimization via Local Bayesian Optimization Samyam Rajbhandari Michael Pearce Jacob R. Gardner Ryan D. Turner Matthias Poloczek 106 474 0 03 Oct 2019
The Differentiable Cross-Entropy Method Brandon Amos Denis Yarats 131 54 0 27 Sep 2019
Sequential Learning of Active Subspaces Nathan Wycoff M. Binois Stefan M. Wild 44 29 0 26 Jul 2019
High-dimensional Bayesian optimization using low-dimensional feature spaces Riccardo Moriconi M. Deisenroth K. S. S. Kumar 212 11 0 27 Feb 2019
On the choice of the low-dimensional domain for global optimization via random embeddings M. Binois D. Ginsbourger O. Roustant 100 62 0 18 Apr 2017
Bayesian Optimization for Synthetic Gene Design Javier I. González Joseph Longworth D. James Neil D. Lawrence 95 80 0 07 May 2015