Ian Osband
Ian Osband
DeepMind
Adresse e-mail validée de google.com - Page d'accueil
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Deep exploration via bootstrapped DQN
I Osband, C Blundell, A Pritzel, B Van Roy
Advances in neural information processing systems, 4026-4034, 2016
5322016
Deep q-learning from demonstrations
T Hester, M Vecerik, O Pietquin, M Lanctot, T Schaul, B Piot, D Horgan, ...
arXiv preprint arXiv:1704.03732, 2017
3132017
Noisy networks for exploration
M Fortunato, MG Azar, B Piot, J Menick, I Osband, A Graves, V Mnih, ...
arXiv preprint arXiv:1706.10295, 2017
3122017
A tutorial on thompson sampling
D Russo, B Van Roy, A Kazerouni, I Osband, Z Wen
arXiv preprint arXiv:1707.02038, 2017
2522017
Minimax regret bounds for reinforcement learning
MG Azar, I Osband, R Munos
arXiv preprint arXiv:1703.05449, 2017
1682017
Generalization and exploration via randomized value functions
I Osband, B Van Roy, Z Wen
International Conference on Machine Learning, 2377-2386, 2016
1502016
Learning from demonstrations for real world reinforcement learning
T Hester, M Vecerik, O Pietquin, M Lanctot, T Schaul, B Piot, A Sendonaris, ...
arXiv preprint arXiv:1704.03732, 2017
1072017
Why is posterior sampling better than optimism for reinforcement learning?
I Osband, B Van Roy
International Conference on Machine Learning, 2701-2710, 2017
932017
Randomized prior functions for deep reinforcement learning
I Osband, J Aslanides, A Cassirer
Advances in Neural Information Processing Systems, 8617-8629, 2018
922018
Deep learning for time series modeling
E Busseti, I Osband, S Wong
Technical report, Stanford University, 1-5, 2012
912012
Deep Exploration via Randomized Value Functions
I Osband
https://searchworks.stanford.edu/view/11891201, 2016
892016
The uncertainty bellman equation and exploration
B O’Donoghue, I Osband, R Munos, V Mnih
International Conference on Machine Learning, 3836-3845, 2018
562018
Model-based reinforcement learning and the eluder dimension
I Osband, B Van Roy
Advances in Neural Information Processing Systems, 1466-1474, 2014
532014
Near-optimal reinforcement learning in factored mdps
I Osband, B Van Roy
Advances in Neural Information Processing Systems, 604-612, 2014
472014
Bootstrapped thompson sampling and deep exploration
I Osband, B Van Roy
arXiv preprint arXiv:1507.00300, 2015
412015
Risk versus Uncertainty in Deep Learning: Bayes, Bootstrap and the Dangers of Dropout
I Osband
http://bayesiandeeplearning.org/papers/BDL_4.pdf, 0
41*
On lower bounds for regret in reinforcement learning
I Osband, B Van Roy
arXiv preprint arXiv:1608.02732, 2016
382016
(More) efficient reinforcement learning via posterior sampling
I Osband, D Russo, B Van Roy
Advances in Neural Information Processing Systems, 3003-3011, 2013
312013
Behaviour suite for reinforcement learning
I Osband, Y Doron, M Hessel, J Aslanides, E Sezener, A Saraiva, ...
arXiv preprint arXiv:1908.03568, 2019
202019
Posterior sampling for reinforcement learning without episodes
I Osband, B Van Roy
arXiv preprint arXiv:1608.02731, 2016
172016
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