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Samuel Daulton

Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization

Oct 18, 2022
Samuel Daulton, Xingchen Wan, David Eriksson, Maximilian Balandat, Michael A. Osborne, Eytan Bakshy

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* To appear in Advances in Neural Information Processing Systems 35, 2022. Code available at: https://github.com/facebookresearch/bo_pr

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Log-Linear-Time Gaussian Processes Using Binary Tree Kernels

Oct 04, 2022
Michael K. Cohen, Samuel Daulton, Michael A. Osborne

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* NeurIPS 2022; 9 pages + appendices

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Robust Multi-Objective Bayesian Optimization Under Input Noise

Feb 16, 2022
Samuel Daulton, Sait Cakmak, Maximilian Balandat, Michael A. Osborne, Enlu Zhou, Eytan Bakshy

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* 41 pages. Code is available at https://github.com/facebookresearch/robust_mobo

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Latency-Aware Neural Architecture Search with Multi-Objective Bayesian Optimization

Jun 25, 2021
David Eriksson, Pierce I-Jen Chuang, Samuel Daulton, Peng Xia, Akshat Shrivastava, Arun Babu, Shicong Zhao, Ahmed Aly, Ganesh Venkatesh, Maximilian Balandat

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* To Appear at the 8th ICML Workshop on Automated Machine Learning, ICML 2021

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Distilled Thompson Sampling: Practical and Efficient Thompson Sampling via Imitation Learning

Dec 08, 2020
Hongseok Namkoong, Samuel Daulton, Eytan Bakshy

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* Offline Reinforcement Learning Workshop at Neural Information Processing Systems, 2020

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