Raul Astudillo

According to our database, Raul Astudillo authored at least 17 papers between 2019 and 2026.

Collaborative distances:

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

2026

Actor-Curator: Co-adaptive Curriculum Learning via Policy-Improvement Bandits for RL Post-Training.

Zhengyao Gu, Jonathan Light, Raul Astudillo, Ziyu Ye, Langzhou He, Henry Peng Zou, Wei Cheng, Santiago Paternain, Philip S. Yu, Yisong Yue

CoRR, February, 2026

2025

Bayesian preference elicitation for decision support in multiobjective optimization.

Felix Huber, Sebastian Rojas-Gonzalez, Raul Astudillo

CoRR, July, 2025

Steering Generative Models with Experimental Data for Protein Fitness Optimization.

Jason Yang, Wenda Chu, Daniel Khalil, Raul Astudillo, Bruce J. Wittmann, Frances H. Arnold, Yisong Yue

CoRR, May, 2025

Preferential Multi-Objective Bayesian Optimization.

Raul Astudillo, Kejun Li, Maegan Tucker, Chu Xin Cheng, Aaron D. Ames, Yisong Yue

Trans. Mach. Learn. Res., 2025

2024

Multi-Attribute Optimization Under Preference Uncertainty.

Bhavik A. Shah, Raul Astudillo, Peter I. Frazier

Proceedings of the Winter Simulation Conference, 2024

Practical Bayesian Algorithm Execution via Posterior Sampling.

Chu Xin Cheng, Raul Astudillo, Thomas A. Desautels, Yisong Yue

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Cost-aware Bayesian Optimization via the Pandora's Box Gittins Index.

Qian Xie, Raul Astudillo, Peter I. Frazier, Ziv Scully, Alexander Terenin

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Bayesian Optimization of Function Networks with Partial Evaluations.

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

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

qEUBO: A Decision-Theoretic Acquisition Function for Preferential Bayesian Optimization.

Raul Astudillo, Zhiyuan (Jerry) Lin, Eytan Bakshy, Peter I. Frazier

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Preference Exploration for Efficient Bayesian Optimization with Multiple Outcomes.

Zhiyuan (Jerry) Lin, Raul Astudillo, Peter I. Frazier, Eytan Bakshy

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Thinking Inside the Box: A Tutorial on Grey-Box Bayesian Optimization.

Raul Astudillo, Peter I. Frazier

Proceedings of the Winter Simulation Conference, 2021

Multi-Step Budgeted Bayesian Optimization with Unknown Evaluation Costs.

Raul Astudillo, Daniel R. Jiang, Maximilian Balandat, Eytan Bakshy, Peter I. Frazier

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

Bayesian Optimization of Function Networks.

Raul Astudillo, Peter I. Frazier

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

2020

Bayesian Optimization of Risk Measures.

Sait Cakmak, Raul Astudillo, Peter I. Frazier, Enlu Zhou

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

Multi-attribute Bayesian optimization with interactive preference learning.

Raul Astudillo, Peter I. Frazier

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Bayesian Optimization with Uncertain Preferences over Attributes.

Raul Astudillo, Peter I. Frazier

CoRR, 2019

Bayesian Optimization of Composite Functions.

Raul Astudillo, Peter I. Frazier

Proceedings of the 36th International Conference on Machine Learning, 2019