@inproceedings{61e5af2048044c6ebe35481190d14d5f,
title = "High-Dimensional Discrete Bayesian Optimization with Intrinsic Dimension",
abstract = "Bayesian optimization (BO) has achieved remarkable success in optimizing low-dimensional continuous problems. Recently, BO in high-dimensional discrete solution space is in demand. However, satisfying BO algorithms tailored to this issue still lack. Fortunately, it is observed that high-dimensional discrete optimization problems may exist low-dimensional intrinsic subspace. Inspired by this observation, this paper proposes a Locality Sensitive Hashing based Bayesian Optimization (LSH-BO) method for high-dimensional discrete functions with intrinsic dimension. Via randomly embedding solutions from intrinsic subspace to original space and discretization, LSH-BO turns high-dimensional discrete optimization problems into low-dimensional continuous ones. Theoretically we prove that, with probability 1, there exists a corresponding optimal solution in the intrinsic subspace. The empirically results on both synthetic functions and binary quadratic programming task verify that LSH-BO surpasses the compared methods and possesses the versatility across low-dimensional and high-dimensional kernels.",
keywords = "Black-box optimization, Intrinsic subspace, Locality sensitive hashing",
author = "Li, \{Shu Jun\} and Mingjia Li and Hong Qian",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 19th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2022 ; Conference date: 10-11-2022 Through 13-11-2022",
year = "2022",
doi = "10.1007/978-3-031-20862-1\_39",
language = "英语",
isbn = "9783031208614",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "534--547",
editor = "Sankalp Khanna and Jian Cao and Quan Bai and Guandong Xu",
booktitle = "PRICAI 2022",
address = "德国",
}