Misha Denil
Misha Denil
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Learning to learn by gradient descent by gradient descent
M Andrychowicz, M Denil, S Gomez, MW Hoffman, D Pfau, T Schaul, ...
Advances in neural information processing systems 29, 2016
Predicting parameters in deep learning
M Denil, B Shakibi, L Dinh, MA Ranzato, N De Freitas
Advances in neural information processing systems 26, 2013
Learning to navigate in complex environments
P Mirowski, R Pascanu, F Viola, H Soyer, AJ Ballard, A Banino, M Denil, ...
International Conference on Learning Representations, 2017
From group to individual labels using deep features
D Kotzias, M Denil, N De Freitas, P Smyth
Proceedings of the 21th ACM SIGKDD international conference on knowledge …, 2015
Noisy activation functions
C Gulcehre, M Moczulski, M Denil, Y Bengio
International conference on machine learning, 3059-3068, 2016
Deep fried convnets
Z Yang, M Moczulski, M Denil, N De Freitas, A Smola, L Song, Z Wang
Proceedings of the IEEE international conference on computer vision, 1476-1483, 2015
Learning to Learn without Gradient Descent by Gradient Descent
NF Yutian Chen, Matthew W. Hoffman, Sergio Gomez Colmenarejo, Misha Denil ...
International Conference on Machine Learning, 2017
Narrowing the gap: Random forests in theory and in practice
M Denil, D Matheson, N De Freitas
International conference on machine learning, 665-673, 2014
Learned optimizers that scale and generalize
O Wichrowska, N Maheswaranathan, MW Hoffman, SG Colmenarejo, ...
International conference on machine learning, 3751-3760, 2017
Learning where to attend with deep architectures for image tracking
M Denil, L Bazzani, H Larochelle, N de Freitas
Neural computation 24 (8), 2151-2184, 2012
Hyperbolic attention networks
C Gulcehre, M Denil, M Malinowski, A Razavi, R Pascanu, KM Hermann, ...
arXiv preprint arXiv:1805.09786, 2018
Extraction of salient sentences from labelled documents
M Denil, A Demiraj, N De Freitas
arXiv preprint arXiv:1412.6815, 2014
Large-scale visual speech recognition
B Shillingford, Y Assael, MW Hoffman, T Paine, C Hughes, U Prabhu, ...
arXiv preprint arXiv:1807.05162, 2018
Overlap versus imbalance
M Denil, T Trappenberg
Advances in Artificial Intelligence: 23rd Canadian Conference on Artificial …, 2010
Scaling data-driven robotics with reward sketching and batch reinforcement learning
S Cabi, SG Colmenarejo, A Novikov, K Konyushkova, S Reed, R Jeong, ...
arXiv preprint arXiv:1909.12200, 2019
Acdc: A structured efficient linear layer
M Moczulski, M Denil, J Appleyard, N de Freitas
arXiv preprint arXiv:1511.05946, 2015
Consistency of online random forests
M Denil, D Matheson, N de Freitas
International Conference on Machine Learning, 2013
Making efficient use of demonstrations to solve hard exploration problems
TL Paine, C Gulcehre, B Shahriari, M Denil, M Hoffman, H Soyer, ...
arXiv preprint arXiv:1909.01387, 2019
Learning to perform physics experiments via deep reinforcement learning
M Denil, P Agrawal, TD Kulkarni, T Erez, P Battaglia, N De Freitas
arXiv preprint arXiv:1611.01843, 2016
Offline learning from demonstrations and unlabeled experience
K Zolna, A Novikov, K Konyushkova, C Gulcehre, Z Wang, Y Aytar, ...
arXiv preprint arXiv:2011.13885, 2020
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