34 citations · 100 across the 25 of their papers we have counts for
4 papers · 2 filters
Online Optimization for Offline Safe Reinforcement Learning
Yassine Chemingui, Aryan Deshwal, Alan Fern +2
We study the problem of Offline Safe Reinforcement Learning (OSRL), where the goal is to learn a reward-maximizing policy from fixed data under a cumulative cost constraint. We pro…
BO4Mob: Bayesian Optimization Benchmarks for High-Dimensional Urban Mobility Problem
Seunghee Ryu, Donghoon Kwon, Seongjin Choi +3
We introduce \textbf{BO4Mob}, a new benchmark framework for high-dimensional Bayesian Optimization (BO), driven by the challenge of origin-destination (OD) travel demand estimation…
COM-BOM: Bayesian Exemplar Search for Efficiently Exploring the Accuracy-Calibration Pareto Frontier
Gaoxiang Luo, Aryan Deshwal
Selecting an optimal set of exemplars is critical for good performance of in-context learning. However, prior exemplar search methods narrowly optimize for predictive accuracy, cri…
Learning Surrogates for Offline Black-Box Optimization via Gradient Matching
Minh Hoang, Azza Fadhel, Aryan Deshwal +2
Offline design optimization problem arises in numerous science and engineering applications including material and chemical design, where expensive online experimentation necessita…