4 citations · 6 across the 3 of their papers we have counts for
4 papers
Adaptive Sampling Quasi-Newton Methods for Zeroth-Order Stochastic Optimization
Raghu Bollapragada, Stefan M. Wild
We consider unconstrained stochastic optimization problems with no available gradient information. Such problems arise in settings from derivative-free simulation optimization to r…
Lookahead Acquisition Functions for Finite-Horizon Time-Dependent Bayesian Optimization and Application to Quantum Optimal Control
S. Ashwin Renganathan, Jeffrey Larson, Stefan M. Wild
We propose a novel Bayesian method to solve the maximization of a time-dependent expensive-to-evaluate stochastic oracle. We are interested in the decision that maximizes the oracl…
Recursive Two-Step Lookahead Expected Payoff for Time-Dependent Bayesian Optimization
S. Ashwin Renganathan, Jeffrey Larson, Stefan Wild
We propose a novel Bayesian method to solve the maximization of a time-dependent expensive-to-evaluate oracle. We are interested in the decision that maximizes the oracle at a fini…
Randomized Derivative-Free Optimization of Noisy Convex Functions
Ruobing Chen, Stefan Wild
We propose STARS, a randomized derivative-free algorithm for unconstrained optimization when the function evaluations are contaminated with random noise. STARS takes dynamic, noise…