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
Advances in neural information processing systems 29, 4026-4034, 2016
7522016
Deep q-learning from demonstrations
T Hester, M Vecerik, O Pietquin, M Lanctot, T Schaul, B Piot, D Horgan, ...
Thirty-second AAAI conference on artificial intelligence, 2018
5232018
Noisy networks for exploration
M Fortunato, MG Azar, B Piot, J Menick, I Osband, A Graves, V Mnih, ...
arXiv preprint arXiv:1706.10295, 2017
4742017
A tutorial on thompson sampling
D Russo, B Van Roy, A Kazerouni, I Osband, Z Wen
arXiv preprint arXiv:1707.02038, 2017
4062017
Minimax regret bounds for reinforcement learning
MG Azar, I Osband, R Munos
International Conference on Machine Learning, 263-272, 2017
3162017
Generalization and exploration via randomized value functions
I Osband, B Van Roy, Z Wen
International Conference on Machine Learning, 2377-2386, 2016
2082016
Randomized prior functions for deep reinforcement learning
I Osband, J Aslanides, A Cassirer
arXiv preprint arXiv:1806.03335, 2018
1622018
Deep Exploration via Randomized Value Functions
I Osband
https://searchworks.stanford.edu/view/11891201, 2016
1492016
Why is posterior sampling better than optimism for reinforcement learning?
I Osband, B Van Roy
International conference on machine learning, 2701-2710, 2017
1372017
Learning from demonstrations for real world reinforcement learning
T Hester, M Vecerik, O Pietquin, M Lanctot, T Schaul, B Piot, A Sendonaris, ...
1332017
Deep learning for time series modeling
E Busseti, I Osband, S Wong
Technical report, Stanford University, 1-5, 2012
1082012
The uncertainty bellman equation and exploration
B O’Donoghue, I Osband, R Munos, V Mnih
International Conference on Machine Learning, 3836-3845, 2018
1012018
Model-based reinforcement learning and the eluder dimension
I Osband, B Van Roy
arXiv preprint arXiv:1406.1853, 2014
902014
Risk versus Uncertainty in Deep Learning: Bayes, Bootstrap and the Dangers of Dropout
I Osband
http://bayesiandeeplearning.org/papers/BDL_4.pdf, 0
76*
Near-optimal reinforcement learning in factored mdps
I Osband, B Van Roy
Advances in Neural Information Processing Systems 27, 604-612, 2014
702014
Behaviour suite for reinforcement learning
I Osband, Y Doron, M Hessel, J Aslanides, E Sezener, A Saraiva, ...
arXiv preprint arXiv:1908.03568, 2019
642019
On lower bounds for regret in reinforcement learning
I Osband, B Van Roy
arXiv preprint arXiv:1608.02732, 2016
592016
Bootstrapped thompson sampling and deep exploration
I Osband, B Van Roy
arXiv preprint arXiv:1507.00300, 2015
592015
(More) efficient reinforcement learning via posterior sampling
I Osband, D Russo, B Van Roy
arXiv preprint arXiv:1306.0940, 2013
452013
Meta-learning of sequential strategies
PA Ortega, JX Wang, M Rowland, T Genewein, Z Kurth-Nelson, ...
arXiv preprint arXiv:1905.03030, 2019
322019
The system can't perform the operation now. Try again later.
Articles 1–20