Clement Gehring
Clement Gehring
Verified email at - Homepage
Cited by
Cited by
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
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
Incremental truncated LSTD
C Gehring, Y Pan, M White
International Joint Conference on Artificial Intelligence, 2016
Robust Reinforcement Learning: A Constrained Game-theoretic Approach
J Yu, C Gehring, F Schäfer, A Anandkumar
Learning for Dynamics and Control, 1242-1254, 2021
Approximate Linear Successor Representation
CA Gehring
Multidisciplinary Conference on Reinforcement Learning and Decision Making …, 2015
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
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
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
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
Adaptable replanning with compressed linear action models for learning from demonstrations
C Gehring, LP Kaelbling, T Lozano-Perez
Conference on Robot Learning (CoRL), 2018
Sparse Coding Applied to Digit Recognition
C Gehring, S Lemay
sibi 1, 1, 2012
Neural differential equations for temperature control in buildings under demand response programs
V Taboga, C Gehring, M Le Cam, H Dagdougui, PL Bacon
Applied Energy 368, 123433, 2024
Do Transformer World Models Give Better Policy Gradients?
M Ma, T Ni, C Gehring, P D'Oro, PL Bacon
arXiv preprint arXiv:2402.05290, 2024
Bridging State and History Representations: Understanding Self-Predictive RL
T Ni, B Eysenbach, E Seyedsalehi, M Ma, C Gehring, A Mahajan, ...
arXiv preprint arXiv:2401.08898, 2024
Course Correcting Koopman Representations
M Fathi, C Gehring, J Pilault, D Kanaa, PL Bacon, R Goroshin
arXiv preprint arXiv:2310.15386, 2023
A Differentiable Sequence Model Perspective on Policy Gradients
M Ma, P D'Oro, T Ni, C Gehring, PL Bacon
Functional Risk Minimization
F Alet, C Gehring, T Lozano-Pérez, JB Tenenbaum, LP Kaelbling
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
The system can't perform the operation now. Try again later.
Articles 1–20