オープン アクセスを義務付けられた論文 - Philip Thomas詳細
一般には非公開: 1 件
Philip S Thomas, Erik Learned-Miller and My Phan's contribution to the Discussion of ‘Estimating means of bounded random variables by betting’by Waudby-Smith and Ramdas
PS Thomas, E Learned-Miller, M Phan
Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2024
委任: US National Science Foundation
一般公開: 31 件
Data-efficient off-policy policy evaluation for reinforcement learning
P Thomas, E Brunskill
International conference on machine learning, 2139-2148, 2016
委任: US National Science Foundation, US Institute of Education Sciences
Preventing undesirable behavior of intelligent machines
P Thomas, B Castro da Silva, A Barto, S Giguere, Y Brun, E Brunskill
Science 366 (6468), 999-1004, 2019
委任: US National Science Foundation, US Department of Education
Optimization and evaluation of a proportional derivative controller for planar arm movement
KM Jagodnik, AJ van den Bogert
Journal of Biomechanics 43 (6), 1086-1091, 2010
委任: US National Institutes of Health
Optimizing for the future in non-stationary mdps
Y Chandak, G Theocharous, S Shankar, M White, S Mahadevan, ...
International Conference on Machine Learning, 1414-1425, 2020
委任: US Department of Defense
Evaluating the performance of reinforcement learning algorithms
S Jordan, Y Chandak, D Cohen, M Zhang, P Thomas
International Conference on Machine Learning, 4962-4973, 2020
委任: US Department of Defense
Training an actor-critic reinforcement learning controller for arm movement using human-generated rewards
KM Jagodnik, PS Thomas, AJ van den Bogert, MS Branicky, RF Kirsch
IEEE Transactions on Neural Systems and Rehabilitation Engineering 25 (10 …, 2017
委任: US National Institutes of Health, US Department of Veterans Affairs
Offline contextual bandits with high probability fairness guarantees
B Metevier, S Giguere, S Brockman, A Kobren, Y Brun, E Brunskill, ...
Advances in neural information processing systems 32, 2019
委任: US National Science Foundation, US Department of Defense
Importance Sampling for Fair Policy Selection.
S Doroudi, PS Thomas, E Brunskill
Grantee Submission, 2017
委任: US National Science Foundation, US Institute of Education Sciences, US …
Universal off-policy evaluation
Y Chandak, S Niekum, B da Silva, E Learned-Miller, E Brunskill, ...
Advances in Neural Information Processing Systems 34, 27475-27490, 2021
委任: US National Science Foundation, US Department of Defense
Fairness guarantees under demographic shift
S Giguere, B Metevier, Y Brun, BC Da Silva, PS Thomas, S Niekum
Proceedings of the 10th International Conference on Learning Representations …, 2022
委任: US National Science Foundation, US Department of Defense
Data-efficient policy evaluation through behavior policy search
JP Hanna, PS Thomas, P Stone, S Niekum
International Conference on Machine Learning, 1394-1403, 2017
委任: US National Science Foundation, US Department of Defense
Using options and covariance testing for long horizon off-policy policy evaluation
Z Guo, PS Thomas, E Brunskill
Advances in Neural Information Processing Systems 30, 2017
委任: US National Science Foundation, US Department of Defense, US Institute of …
Application of the Actor-Critic Architecture to Functional Electrical Stimulation Control of a Human Arm.
PS Thomas, AJ van den Bogert, KM Jagodnik, MS Branicky
IAAI, 2009
委任: US National Institutes of Health
Towards safe policy improvement for non-stationary MDPs
Y Chandak, S Jordan, G Theocharous, M White, PS Thomas
Advances in Neural Information Processing Systems 33, 9156-9168, 2020
委任: US National Science Foundation, US Department of Defense, Natural Sciences …
Human-like rewards to train a reinforcement learning controller for planar arm movement
KM Jagodnik, PS Thomas, AJ van den Bogert, MS Branicky, RF Kirsch
IEEE Transactions on Human-Machine Systems 46 (5), 723-733, 2016
委任: US National Institutes of Health, US Department of Veterans Affairs
Energetic natural gradient descent
P Thomas, BC Silva, C Dann, E Brunskill
International Conference on Machine Learning, 2887-2895, 2016
委任: US National Science Foundation, US Institute of Education Sciences
Multi-objective spibb: Seldonian offline policy improvement with safety constraints in finite mdps
PS Thomas, J Pineau, R Laroche
Advances in Neural Information Processing Systems 34, 2004-2017, 2021
委任: US National Science Foundation, Natural Sciences and Engineering Research …
Towards practical mean bounds for small samples
M Phan, P Thomas, E Learned-Miller
International Conference on Machine Learning, 8567-8576, 2021
委任: US National Science Foundation, US Department of Defense
Asynchronous coagent networks
J Kostas, C Nota, P Thomas
International Conference on Machine Learning, 5426-5435, 2020
委任: US Department of Defense
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