Yash Chandak
Title
Cited by
Cited by
Year
Learning action representations for reinforcement learning
Y Chandak, G Theocharous, J Kostas, S Jordan, PS Thomas
arXiv preprint arXiv:1902.00183, 2019
272019
Fusion graph convolutional networks
P Vijayan, Y Chandak, MM Khapra, S Parthasarathy, B Ravindran
arXiv preprint arXiv:1805.12528, 2018
32018
On optimizing human-machine task assignments
A Veit, M Wilber, R Vaish, S Belongie, J Davis, V Anand, A Aviral, ...
arXiv preprint arXiv:1509.07543, 2015
32015
Optimizing for the Future in Non-Stationary MDPs
Y Chandak, G Theocharous, S Shankar, S Mahadevan, M White, ...
arXiv preprint arXiv:2005.08158, 2020
12020
Reinforcement Learning When All Actions Are Not Always Available.
Y Chandak, G Theocharous, B Metevier, PS Thomas
AAAI, 3381-3388, 2020
12020
Lifelong Learning with a Changing Action Set.
Y Chandak, G Theocharous, C Nota, PS Thomas
AAAI, 3373-3380, 2020
12020
Evaluating the Performance of Reinforcement Learning Algorithms
SM Jordan, Y Chandak, D Cohen, M Zhang, PS Thomas
arXiv preprint arXiv:2006.16958, 2020
2020
Classical Policy Gradient: Preserving Bellman's Principle of Optimality
PS Thomas, SM Jordan, Y Chandak, C Nota, J Kostas
arXiv preprint arXiv:1906.03063, 2019
2019
HOPF: Higher Order Propagation Framework for Deep Collective Classification
P Vijayan, Y Chandak, MM Khapra, S Parthasarathy, B Ravindran
arXiv preprint arXiv:1805.12421, 2018
2018
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