Scalable Bayesian Optimization with Sparse Gaussian Process Models

This thesis focuses on Bayesian optimization with the improvements coming from two aspects:(i) the use of derivative information to accelerate the optimization convergence; and (ii) the consideration of scalable GPs for handling massive data.

cs.LG cs.IR stat.ML Gaussian Processes and Bayesian Inference Advanced Multi-Objective Optimization Algorithms Advanced Bandit Algorithms Research Computer Science Mathematics

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References (100)

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Scalable Bayesian Optimization via Focalized Sparse Gaussian ProcessesYunyue Wei, Vincent Zhuang, Saraswati Soedarmadji et al.2024 · Neural Information Processing Systems · 7 citations In Library

Sparse Spectrum Gaussian Process for Bayesian OptimizationAng Yang, Cheng Li, Santu Rana et al.2019 · Pacific-Asia Conference on Knowledge Discovery and Data Mining · 6 citations In Library

Global Optimization on Graph-Structured Data via Gaussian Processes with Spectral RepresentationsShu Hong, Yongsheng Mei, Mahdi Imani et al.2025 · arXiv.org · 1 citation In Library

Bayesian Hybrid Model Search and Averaging for Sparse Gaussian Process RegressionWeikang Duan, Gyuhyeong Goh2025 · Statistical Analysis and Data Mining The ASA Data Science Journal · 0 citations In Library

Learning Gaussian Processes with Bayesian Posterior OptimizationLuiz F. O. Chamon, Santiago Paternain, Alejandro Ribeiro2019 · Asilomar Conference on Signals, Systems and Computers · 0 citations In Library

Understanding and Comparing Scalable Gaussian Process Regression for Big DataHaitao Liu, Jianfei Cai, Y. Ong et al.2018 · Knowledge-Based Systems · 34 citations In Library

Scalable Bayesian Optimization Using Deep Neural NetworksJasper Snoek, Oren Rippel, Kevin Swersky et al.2015 · International Conference on Machine Learning · 1.1k citations In Library

Transfer Learning with Gaussian Processes for Bayesian OptimizationPetru Tighineanu, Kathrin Skubch, Paul Baireuther et al.2021 · arXiv (Cornell University) · 44 citations In Library

When Gaussian Process Meets Big Data: A Review of Scalable GPsHaitao Liu, Yew-Soon Ong, Xiaobo Shen et al.2020 · IEEE Transactions on Neural Networks and Learning Systems In Library

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Scalable Bayesian Optimization with Sparse Gaussian Process Models

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