关注
Harshat Kumar
Harshat Kumar
Johns Hopkins University Applied Physics Laboratory
在 jhuapl.edu 的电子邮件经过验证
标题
引用次数
引用次数
年份
On the sample complexity of actor-critic method for reinforcement learning with function approximation
H Kumar, A Koppel, A Ribeiro
Machine Learning 112 (7), 2433-2467, 2023
1052023
A joint design approach for spectrum sharing between radar and communication systems
B Li, H Kumar, AP Petropulu
2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016
462016
Navigation of a quadratic potential with ellipsoidal obstacles
H Kumar, S Paternain, A Ribeiro
Automatica 146, 110643, 2022
182022
Zeroth-order deterministic policy gradient
H Kumar, DS Kalogerias, GJ Pappas, A Ribeiro
arXiv preprint arXiv:2006.07314, 2020
142020
Navigation of a quadratic potential with star obstacles
H Kumar, S Paternain, A Ribeiro
2020 American Control Conference (ACC), 2043-2048, 2020
72020
Fusion-Id: A Photoplethysmography and Motion Sensor Fusion Biometric Authenticator With Few-Shot on-Boarding
H Kumar, HS Mousavi, B Shahsavari
ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022
32022
Lie group algebra convolutional filters
H Kumar, A Parada-Mayorga, A Ribeiro
IEEE Transactions on Signal Processing, 2024
22024
Actor-only deterministic policy gradient via zeroth-order gradient oracles in action space
H Kumar, DS Kalogerias, GJ Pappas, A Ribeiro
2021 IEEE International Symposium on Information Theory (ISIT), 1676-1681, 2021
22021
On the sample complexity of actor-critic for reinforcement learning
H Kumar, A Koppel, A Ribeiro
Conference on Neural Information Processing Systems (NeurIPS), 2019
22019
Algebraic convolutional filters on lie group algebras
H Kumar, A Parada-Mayorga, A Ribeiro
ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023
12023
Leveraging Models to Improve Data Efficiency: Navigation, Reinforcement Learning, and Lie Group Convolutions
H Kumar
University of Pennsylvania, 2023
2023
Parameter Critic: a Model Free Variance Reduction Method Through Imperishable Samples
J Cervino, H Kumar, A Ribeiro
arXiv preprint arXiv:2009.13668, 2020
2020
It’s Over 400: Cooperative reinforcement learning through self-play
H Elzayn, M Fereydounian, M Hayhoe, H Kumar, S Sun, G Simulator, ...
Hidden Information, Teamwork, and Prediction in Trick-Taking Card Games
H Elzayn, M Hayhoe, H Kumar, M Fereydounian
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