500 citations · 2.4k across the 118 of their papers we have counts for
5 papers · 1 filter
Advanced Manufacturing Configuration by Sample-efficient Batch Bayesian Optimization
Xavier Guidetti, Alisa Rupenyan, Lutz Fassl +2
We propose a framework for the configuration and operation of expensive-to-evaluate advanced manufacturing methods, based on Bayesian optimization. The framework unifies a tailored…
PAGE-PG: A Simple and Loopless Variance-Reduced Policy Gradient Method with Probabilistic Gradient Estimation
Matilde Gargiani, Andrea Zanelli, Andrea Martinelli +2
Despite their success, policy gradient methods suffer from high variance of the gradient estimate, which can result in unsatisfactory sample complexity. Recently, numerous variance…
Stochastic convex optimization for provably efficient apprenticeship learning
Angeliki Kamoutsi, Goran Banjac, John Lygeros
We consider large-scale Markov decision processes (MDPs) with an unknown cost function and employ stochastic convex optimization tools to address the problem of imitation learning,…
Efficient Performance Bounds for Primal-Dual Reinforcement Learning from Demonstrations
Angeliki Kamoutsi, Goran Banjac, John Lygeros
We consider large-scale Markov decision processes with an unknown cost function and address the problem of learning a policy from a finite set of expert demonstrations. We assume t…
Physics-informed linear regression is competitive with two Machine Learning methods in residential building MPC
Felix Bünning, Benjamin Huber, Adrian Schalbetter +5
Because physics-based building models are difficult to obtain as each building is individual, there is an increasing interest in generating models suitable for building MPC directl…