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Samuel Daulton
Publication Activity (10 Years)
Years Active: 2017-2023
Publications (10 Years): 25
Top Topics
Optimization Process
Monte Carlo Sampling
Gaussian Processes
Conflicting Objectives
Top Venues
CoRR
NeurIPS
ICML
ICASSP
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Publications
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Poompol Buathong
,
Jiayue Wan
,
Samuel Daulton
,
Raul Astudillo
,
Maximilian Balandat
,
Peter I. Frazier
Bayesian Optimization of Function Networks with Partial Evaluations.
CoRR
(2023)
Samuel Daulton
,
Maximilian Balandat
,
Eytan Bakshy
Hypervolume Knowledge Gradient: A Lookahead Approach for Multi-Objective Bayesian Optimization with Partial Information.
ICML
(2023)
Sebastian Ament
,
Samuel Daulton
,
David Eriksson
,
Maximilian Balandat
,
Eytan Bakshy
Unexpected Improvements to Expected Improvement for Bayesian Optimization.
NeurIPS
(2023)
Sebastian Ament
,
Samuel Daulton
,
David Eriksson
,
Maximilian Balandat
,
Eytan Bakshy
Unexpected Improvements to Expected Improvement for Bayesian Optimization.
CoRR
(2023)
Michael K. Cohen
,
Samuel Daulton
,
Michael A. Osborne
Log-Linear-Time Gaussian Processes Using Binary Tree Kernels.
NeurIPS
(2022)
Samuel Daulton
,
David Eriksson
,
Maximilian Balandat
,
Eytan Bakshy
Multi-objective Bayesian optimization over high-dimensional search spaces.
UAI
(2022)
Samuel Daulton
,
Xingchen Wan
,
David Eriksson
,
Maximilian Balandat
,
Michael A. Osborne
,
Eytan Bakshy
Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization.
NeurIPS
(2022)
Samuel Daulton
,
Sait Cakmak
,
Maximilian Balandat
,
Michael A. Osborne
,
Enlu Zhou
,
Eytan Bakshy
Robust Multi-Objective Bayesian Optimization Under Input Noise.
ICML
(2022)
Samuel Daulton
,
Sait Cakmak
,
Maximilian Balandat
,
Michael A. Osborne
,
Enlu Zhou
,
Eytan Bakshy
Robust Multi-Objective Bayesian Optimization Under Input Noise.
CoRR
(2022)
Samuel Daulton
,
Xingchen Wan
,
David Eriksson
,
Maximilian Balandat
,
Michael A. Osborne
,
Eytan Bakshy
Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization.
CoRR
(2022)
Michael K. Cohen
,
Samuel Daulton
,
Michael A. Osborne
Log-Linear-Time Gaussian Processes Using Binary Tree Kernels.
CoRR
(2022)
Samuel Daulton
,
David Eriksson
,
Maximilian Balandat
,
Eytan Bakshy
Multi-Objective Bayesian Optimization over High-Dimensional Search Spaces.
CoRR
(2021)
Ryan M. Dreifuerst
,
Samuel Daulton
,
Yuchen Qian
,
Paul Varkey
,
Maximilian Balandat
,
Sanjay Kasturia
,
Anoop Tomar
,
Ali Yazdan
,
Vish Ponnampalam
,
Robert W. Heath Jr.
Optimizing Coverage and Capacity in Cellular Networks using Machine Learning.
ICASSP
(2021)
David Eriksson
,
Pierce I-Jen Chuang
,
Samuel Daulton
,
Peng Xia
,
Akshat Shrivastava
,
Arun Babu
,
Shicong Zhao
,
Ahmed Aly
,
Ganesh Venkatesh
,
Maximilian Balandat
Latency-Aware Neural Architecture Search with Multi-Objective Bayesian Optimization.
CoRR
(2021)
Samuel Daulton
,
Maximilian Balandat
,
Eytan Bakshy
Parallel Bayesian Optimization of Multiple Noisy Objectives with Expected Hypervolume Improvement.
NeurIPS
(2021)
Samuel Daulton
,
Maximilian Balandat
,
Eytan Bakshy
Parallel Bayesian Optimization of Multiple Noisy Objectives with Expected Hypervolume Improvement.
CoRR
(2021)
Ryan M. Dreifuerst
,
Samuel Daulton
,
Yuchen Qian
,
Paul Varkey
,
Maximilian Balandat
,
Sanjay Kasturia
,
Anoop Tomar
,
Ali Yazdan
,
Vish Ponnampalam
,
Robert W. Heath Jr.
Optimizing Coverage and Capacity in Cellular Networks using Machine Learning.
CoRR
(2020)
Hongseok Namkoong
,
Samuel Daulton
,
Eytan Bakshy
Distilled Thompson Sampling: Practical and Efficient Thompson Sampling via Imitation Learning.
CoRR
(2020)
Samuel Daulton
,
Maximilian Balandat
,
Eytan Bakshy
Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization.
CoRR
(2020)
Maximilian Balandat
,
Brian Karrer
,
Daniel R. Jiang
,
Samuel Daulton
,
Benjamin Letham
,
Andrew Gordon Wilson
,
Eytan Bakshy
BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization.
NeurIPS
(2020)
Samuel Daulton
,
Maximilian Balandat
,
Eytan Bakshy
Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization.
NeurIPS
(2020)
Maximilian Balandat
,
Brian Karrer
,
Daniel R. Jiang
,
Samuel Daulton
,
Benjamin Letham
,
Andrew Gordon Wilson
,
Eytan Bakshy
BoTorch: Programmable Bayesian Optimization in PyTorch.
CoRR
(2019)
Samuel Daulton
,
Shaun Singh
,
Vashist Avadhanula
,
Drew Dimmery
,
Eytan Bakshy
Thompson Sampling for Contextual Bandit Problems with Auxiliary Safety Constraints.
CoRR
(2019)
Taylor W. Killian
,
Samuel Daulton
,
Finale Doshi-Velez
,
George Dimitri Konidaris
Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes.
NIPS
(2017)
Taylor W. Killian
,
Samuel Daulton
,
George Dimitri Konidaris
,
Finale Doshi-Velez
Robust and Efficient Transfer Learning with Hidden-Parameter Markov Decision Processes.
CoRR
(2017)