Search Results for author:
Found 2 papers, 1 papers with code
Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo is All you Need
We leverage multilevel Monte Carlo (MLMC) to improve the performance of multi-step look-ahead Bayesian optimization (BO) methods that involve nested expectations and maximizations.
Exponential Concentration in Stochastic Approximation
We apply our results to several different Stochastic Approximation algorithms, specifically Projected Stochastic Gradient Descent, Kiefer-Wolfowitz and Stochastic Frank-Wolfe algorithms.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
