Clement Gehring
Clement Gehring
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Batched large-scale bayesian optimization in high-dimensional spaces
Z Wang, C Gehring, P Kohli, S Jegelka
International Conference on Artificial Intelligence and Statistics, 745-754, 2018
Smart exploration in reinforcement learning using absolute temporal difference errors
C Gehring, D Precup
Proceedings of the 2013 international conference on Autonomous agents and …, 2013
Incremental truncated LSTD
C Gehring, Y Pan, M White
International Joint Conference on Artificial Intelligence, 2016
Approximate Linear Successor Representation
CA Gehring
Multidisciplinary Conference on Reinforcement Learning and Decision Making …, 2015
Reinforcement Learning for Classical Planning: Viewing Heuristics as Dense Reward Generators
C Gehring, M Asai, R Chitnis, T Silver, LP Kaelbling, S Sohrabi, M Katz
arXiv, 2021
Reinforcement Learning Competition: Helicopter Hovering with Controllability and Kernel-Based Stochastic Factorization
A Asbah, AMS Barreto, C Gehring, J Pineau, D Precup
Proceedings of International Conference on Machine Learning (ICML …, 2013
Comment on “Giant electromechanical coupling of relaxor ferroelectrics controlled by polar nanoregion vibrations”
PM Gehring, Z Xu, C Stock, G Xu, D Parshall, L Harriger, CA Gehring, X Li, ...
Science advances 5 (3), eaar5066, 2019
A Lagrangian Method for Inverse Problems in Reinforcement Learning
PL Bacon, F Schäfer, C Gehring, A Anandkumar, E Brunskill
NeurIPS Optimization Foundations for Reinforcement Learning Workshop, 2019
Sparse Coding Applied to Digit Recognition
C Gehring, S Lemay
sibi 1, 1, 2012
Robust Reinforcement Learning: A Constrained Game-theoretic Approach
J Yu, C Gehring, F Schäfer, A Anandkumar
Learning for Dynamics and Control, 1242-1254, 2021
Adaptable replanning with compressed linear action models for learning from demonstrations
C Gehring, LP Kaelbling, T Lozano-Perez
Conference on Robot Learning (CoRL), 2018
Understanding End-to-End Model-Based Reinforcement Learning Methods as Implicit Parameterization
C Gehring, K Kawaguchi, J Huang, L Kaelbling
Advances in Neural Information Processing Systems 34, 703-714, 2021
Efficient reinforcement learning via singular value decomposition, end-to-end model-based methods and reward shaping
C Gehring
Massachusetts Institute of Technology, 2022
Shape Fitting Temporal Difference Learning
C Gehring
McGill University (Canada), 2015
Motion Planning using Naturally Annoying Grammars (NAGs)
CR Garrett, C Gehring, G Goretkin, Z Mariet, Z Wang
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