Ian Osband
Ian Osband
DeepMind
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
Deep exploration via bootstrapped DQN
I Osband, C Blundell, A Pritzel, B Van Roy
arXiv preprint arXiv:1602.04621, 2016
6862016
Deep q-learning from demonstrations
T Hester, M Vecerik, O Pietquin, M Lanctot, T Schaul, B Piot, D Horgan, ...
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
4492018
Noisy networks for exploration
M Fortunato, MG Azar, B Piot, J Menick, I Osband, A Graves, V Mnih, ...
arXiv preprint arXiv:1706.10295, 2017
4232017
A tutorial on thompson sampling
D Russo, B Van Roy, A Kazerouni, I Osband, Z Wen
arXiv preprint arXiv:1707.02038, 2017
3522017
Minimax regret bounds for reinforcement learning
MG Azar, I Osband, R Munos
International Conference on Machine Learning, 263-272, 2017
2692017
Generalization and exploration via randomized value functions
I Osband, B Van Roy, Z Wen
International Conference on Machine Learning, 2377-2386, 2016
1932016
Randomized prior functions for deep reinforcement learning
I Osband, J Aslanides, A Cassirer
arXiv preprint arXiv:1806.03335, 2018
1432018
Deep Exploration via Randomized Value Functions
I Osband
https://searchworks.stanford.edu/view/11891201, 2016
1302016
Learning from demonstrations for real world reinforcement learning
T Hester, M Vecerik, O Pietquin, M Lanctot, T Schaul, B Piot, A Sendonaris, ...
1252017
Why is posterior sampling better than optimism for reinforcement learning?
I Osband, B Van Roy
International Conference on Machine Learning, 2701-2710, 2017
1192017
Deep learning for time series modeling
E Busseti, I Osband, S Wong
Technical report, Stanford University, 1-5, 2012
1022012
The uncertainty bellman equation and exploration
B O’Donoghue, I Osband, R Munos, V Mnih
International Conference on Machine Learning, 3836-3845, 2018
852018
Model-based reinforcement learning and the eluder dimension
I Osband, B Van Roy
arXiv preprint arXiv:1406.1853, 2014
772014
Near-optimal reinforcement learning in factored mdps
I Osband, B Van Roy
arXiv preprint arXiv:1403.3741, 2014
682014
Risk versus Uncertainty in Deep Learning: Bayes, Bootstrap and the Dangers of Dropout
I Osband
http://bayesiandeeplearning.org/papers/BDL_4.pdf, 0
66*
Behaviour suite for reinforcement learning
I Osband, Y Doron, M Hessel, J Aslanides, E Sezener, A Saraiva, ...
arXiv preprint arXiv:1908.03568, 2019
552019
Bootstrapped thompson sampling and deep exploration
I Osband, B Van Roy
arXiv preprint arXiv:1507.00300, 2015
542015
On lower bounds for regret in reinforcement learning
I Osband, B Van Roy
arXiv preprint arXiv:1608.02732, 2016
522016
(More) efficient reinforcement learning via posterior sampling
I Osband, D Russo, B Van Roy
arXiv preprint arXiv:1306.0940, 2013
412013
Meta-learning of sequential strategies
PA Ortega, JX Wang, M Rowland, T Genewein, Z Kurth-Nelson, ...
arXiv preprint arXiv:1905.03030, 2019
302019
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