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2020 – today
- 2022
[i17]Alex Lamb, Riashat Islam, Yonathan Efroni, Aniket Didolkar, Dipendra Misra, Dylan J. Foster, Lekan Molu, Rajan Chari, Akshay Krishnamurthy, John Langford:
Guaranteed Discovery of Controllable Latent States with Multi-Step Inverse Models. CoRR abs/2207.08229 (2022)- 2021
- [i16]Samin Yeasar Arnob, Riashat Islam, Doina Precup:
Importance of Empirical Sample Complexity Analysis for Offline Reinforcement Learning. CoRR abs/2112.15578 (2021)
2010 – 2019
- 2019
- [c3]Anirudh Goyal, Riashat Islam, Daniel Strouse, Zafarali Ahmed, Hugo Larochelle, Matthew M. Botvinick, Yoshua Bengio, Sergey Levine:
InfoBot: Transfer and Exploration via the Information Bottleneck. ICLR (Poster) 2019 - [i15]Anirudh Goyal, Riashat Islam, Daniel Strouse, Zafarali Ahmed, Matthew M. Botvinick, Hugo Larochelle, Sergey Levine, Yoshua Bengio:
InfoBot: Transfer and Exploration via the Information Bottleneck. CoRR abs/1901.10902 (2019) - [i14]Disha Shrivastava, Eeshan Gunesh Dhekane, Riashat Islam:
Transfer Learning by Modeling a Distribution over Policies. CoRR abs/1906.03574 (2019) - [i13]Riashat Islam, Komal K. Teru, Deepak Sharma:
Off-Policy Policy Gradient Algorithms by Constraining the State Distribution Shift. CoRR abs/1911.06970 (2019) - [i12]Riashat Islam, Raihan Seraj, Pierre-Luc Bacon, Doina Precup:
Entropy Regularization with Discounted Future State Distribution in Policy Gradient Methods. CoRR abs/1912.05104 (2019) - [i11]Riashat Islam, Raihan Seraj, Samin Yeasar Arnob, Doina Precup:
Doubly Robust Off-Policy Actor-Critic Algorithms for Reinforcement Learning. CoRR abs/1912.05109 (2019) - [i10]Riashat Islam, Zafarali Ahmed, Doina Precup:
Marginalized State Distribution Entropy Regularization in Policy Optimization. CoRR abs/1912.05128 (2019) - 2018
- [j1]Vincent François-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joelle Pineau:
An Introduction to Deep Reinforcement Learning. Found. Trends Mach. Learn. 11(3-4): 219-354 (2018) - [c2]Peter Henderson, Riashat Islam, Philip Bachman, Joelle Pineau, Doina Precup, David Meger:
Deep Reinforcement Learning That Matters. AAAI 2018: 3207-3214 - [i9]Philip Bachman, Riashat Islam, Alessandro Sordoni, Zafarali Ahmed:
VFunc: a Deep Generative Model for Functions. CoRR abs/1807.04106 (2018) - [i8]Arash Tavakoli, Vitaly Levdik, Riashat Islam, Petar Kormushev:
Prioritizing Starting States for Reinforcement Learning. CoRR abs/1811.11298 (2018) - [i7]Vincent François-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joelle Pineau:
An Introduction to Deep Reinforcement Learning. CoRR abs/1811.12560 (2018) - 2017
- [c1]Yarin Gal, Riashat Islam, Zoubin Ghahramani:
Deep Bayesian Active Learning with Image Data. ICML 2017: 1183-1192 - [i6]Yarin Gal, Riashat Islam, Zoubin Ghahramani:
Deep Bayesian Active Learning with Image Data. CoRR abs/1703.02910 (2017) - [i5]Riashat Islam, Peter Henderson, Maziar Gomrokchi, Doina Precup:
Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control. CoRR abs/1708.04133 (2017) - [i4]Peter Henderson, Riashat Islam, Philip Bachman, Joelle Pineau, Doina Precup, David Meger:
Deep Reinforcement Learning that Matters. CoRR abs/1709.06560 (2017) - [i3]David Krueger, Chin-Wei Huang, Riashat Islam, Ryan Turner, Alexandre Lacoste, Aaron C. Courville:
Bayesian Hypernetworks. CoRR abs/1710.04759 (2017) - [i2]Bogdan Mazoure, Riashat Islam:
Alpha-Divergences in Variational Dropout. CoRR abs/1711.04345 (2017) - [i1]Peter Henderson, Thang Doan, Riashat Islam, David Meger:
Bayesian Policy Gradients via Alpha Divergence Dropout Inference. CoRR abs/1712.02037 (2017)
Coauthor Index
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