102 citations · 105 across the 4 of their papers we have counts for
4 papers
Functional Risk Minimization
Ferran Alet, Clement Gehring, Tomás Lozano-Pérez +3
The field of Machine Learning has changed significantly since the 1970s. However, its most basic principle, Empirical Risk Minimization (ERM), remains unchanged. We propose Functio…
Reinforcement Learning for Classical Planning: Viewing Heuristics as Dense Reward Generators
Clement Gehring, Masataro Asai, Rohan Chitnis +4
Recent advances in reinforcement learning (RL) have led to a growing interest in applying RL to classical planning domains or applying classical planning methods to some complex RL…
Batched Large-scale Bayesian Optimization in High-dimensional Spaces
Zi Wang, Clement Gehring, Pushmeet Kohli +1
Bayesian optimization (BO) has become an effective approach for black-box function optimization problems when function evaluations are expensive and the optimum can be achieved wit…
Incremental Truncated LSTD
Clement Gehring, Yangchen Pan, Martha White
Balancing between computational efficiency and sample efficiency is an important goal in reinforcement learning. Temporal difference (TD) learning algorithms stochastically update…