Samuel Daulton

According to our database, Samuel Daulton authored at least 16 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Bayesian Optimization of Function Networks with Partial Evaluations.

Poompol Buathong, Jiayue Wan, Samuel Daulton, Raul Astudillo, Maximilian Balandat, Peter I. Frazier

CoRR, 2023

Unexpected Improvements to Expected Improvement for Bayesian Optimization.

Sebastian Ament, Samuel Daulton, David Eriksson, Maximilian Balandat, Eytan Bakshy

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Hypervolume Knowledge Gradient: A Lookahead Approach for Multi-Objective Bayesian Optimization with Partial Information.

Samuel Daulton, Maximilian Balandat, Eytan Bakshy

Proceedings of the International Conference on Machine Learning, 2023

2022

Multi-objective Bayesian optimization over high-dimensional search spaces.

Samuel Daulton, David Eriksson, Maximilian Balandat, Eytan Bakshy

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization.

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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Log-Linear-Time Gaussian Processes Using Binary Tree Kernels.

Michael K. Cohen, Samuel Daulton, Michael A. Osborne

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Robust Multi-Objective Bayesian Optimization Under Input Noise.

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

Proceedings of the International Conference on Machine Learning, 2022

2021

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

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

CoRR, 2021

Parallel Bayesian Optimization of Multiple Noisy Objectives with Expected Hypervolume Improvement.

Samuel Daulton, Maximilian Balandat, Eytan Bakshy

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Optimizing Coverage and Capacity in Cellular Networks using Machine Learning.

Ryan M. Dreifuerst, Samuel Daulton, Yuchen Qian, Paul Varkey, Maximilian Balandat, Sanjay Kasturia, Anoop Tomar, Ali Yazdan, Vish Ponnampalam, Robert W. Heath Jr.

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

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

Hongseok Namkoong, Samuel Daulton, Eytan Bakshy

CoRR, 2020

Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization.

Samuel Daulton, Maximilian Balandat, Eytan Bakshy

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization.

Maximilian Balandat, Brian Karrer, Daniel R. Jiang, Samuel Daulton, Benjamin Letham, Andrew Gordon Wilson, Eytan Bakshy

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Thompson Sampling for Contextual Bandit Problems with Auxiliary Safety Constraints.

Samuel Daulton, Shaun Singh, Vashist Avadhanula, Drew Dimmery, Eytan Bakshy

CoRR, 2019

BoTorch: Programmable Bayesian Optimization in PyTorch.

Maximilian Balandat, Brian Karrer, Daniel R. Jiang, Samuel Daulton, Benjamin Letham, Andrew Gordon Wilson, Eytan Bakshy

CoRR, 2019

2017

Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes.

Taylor W. Killian, Samuel Daulton, Finale Doshi-Velez, George Dimitri Konidaris

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017