Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox

Picture for Misha Denil

Offline Learning from Demonstrations and Unlabeled Experience


Nov 27, 2020
Konrad Zolna, Alexander Novikov, Ksenia Konyushkova, Caglar Gulcehre, Ziyu Wang, Yusuf Aytar, Misha Denil, Nando de Freitas, Scott Reed

* Accepted to Offline Reinforcement Learning Workshop at Neural Information Processing Systems (2020) 

  Access Paper or Ask Questions

Large-scale multilingual audio visual dubbing


Nov 06, 2020
Yi Yang, Brendan Shillingford, Yannis Assael, Miaosen Wang, Wendi Liu, Yutian Chen, Yu Zhang, Eren Sezener, Luis C. Cobo, Misha Denil, Yusuf Aytar, Nando de Freitas

* 26 pages, 8 figures 

  Access Paper or Ask Questions

Positive-Unlabeled Reward Learning


Nov 01, 2019
Danfei Xu, Misha Denil


  Access Paper or Ask Questions

Task-Relevant Adversarial Imitation Learning


Oct 02, 2019
Konrad Zolna, Scott Reed, Alexander Novikov, Sergio Gomez Colmenarej, David Budden, Serkan Cabi, Misha Denil, Nando de Freitas, Ziyu Wang


  Access Paper or Ask Questions

A Framework for Data-Driven Robotics


Sep 26, 2019
Serkan Cabi, Sergio G贸mez Colmenarejo, Alexander Novikov, Ksenia Konyushkova, Scott Reed, Rae Jeong, Konrad 呕o艂na, Yusuf Aytar, David Budden, Mel Vecerik, Oleg Sushkov, David Barker, Jonathan Scholz, Misha Denil, Nando de Freitas, Ziyu Wang


  Access Paper or Ask Questions

Making Efficient Use of Demonstrations to Solve Hard Exploration Problems


Sep 03, 2019
Tom Le Paine, Caglar Gulcehre, Bobak Shahriari, Misha Denil, Matt Hoffman, Hubert Soyer, Richard Tanburn, Steven Kapturowski, Neil Rabinowitz, Duncan Williams, Gabriel Barth-Maron, Ziyu Wang, Nando de Freitas, Worlds Team


  Access Paper or Ask Questions

Hyperbolic Attention Networks


May 24, 2018
Caglar Gulcehre, Misha Denil, Mateusz Malinowski, Ali Razavi, Razvan Pascanu, Karl Moritz Hermann, Peter Battaglia, Victor Bapst, David Raposo, Adam Santoro, Nando de Freitas


  Access Paper or Ask Questions

Learning Awareness Models


Apr 17, 2018
Brandon Amos, Laurent Dinh, Serkan Cabi, Thomas Roth枚rl, Sergio G贸mez Colmenarejo, Alistair Muldal, Tom Erez, Yuval Tassa, Nando de Freitas, Misha Denil

* Accepted to ICLR 2018 

  Access Paper or Ask Questions

Learned Optimizers that Scale and Generalize


Sep 07, 2017
Olga Wichrowska, Niru Maheswaranathan, Matthew W. Hoffman, Sergio Gomez Colmenarejo, Misha Denil, Nando de Freitas, Jascha Sohl-Dickstein

* Final ICML paper after reviewer suggestions 

  Access Paper or Ask Questions

Learning to Perform Physics Experiments via Deep Reinforcement Learning


Aug 17, 2017
Misha Denil, Pulkit Agrawal, Tejas D Kulkarni, Tom Erez, Peter Battaglia, Nando de Freitas


  Access Paper or Ask Questions

The Intentional Unintentional Agent: Learning to Solve Many Continuous Control Tasks Simultaneously


Jul 11, 2017
Serkan Cabi, Sergio G贸mez Colmenarejo, Matthew W. Hoffman, Misha Denil, Ziyu Wang, Nando de Freitas


  Access Paper or Ask Questions

Programmable Agents


Jun 20, 2017
Misha Denil, Sergio G贸mez Colmenarejo, Serkan Cabi, David Saxton, Nando de Freitas


  Access Paper or Ask Questions

Learning to Learn without Gradient Descent by Gradient Descent


Jun 12, 2017
Yutian Chen, Matthew W. Hoffman, Sergio Gomez Colmenarejo, Misha Denil, Timothy P. Lillicrap, Matt Botvinick, Nando de Freitas

* Accepted by ICML 2017. Previous version "Learning to Learn for Global Optimization of Black Box Functions" was published in the Deep Reinforcement Learning Workshop, NIPS 2016 

  Access Paper or Ask Questions

Learning to Navigate in Complex Environments


Jan 13, 2017
Piotr Mirowski, Razvan Pascanu, Fabio Viola, Hubert Soyer, Andrew J. Ballard, Andrea Banino, Misha Denil, Ross Goroshin, Laurent Sifre, Koray Kavukcuoglu, Dharshan Kumaran, Raia Hadsell

* 11 pages, 5 appendix pages, 11 figures, 3 tables, under review as a conference paper at ICLR 2017 

  Access Paper or Ask Questions

Learning to learn by gradient descent by gradient descent


Nov 30, 2016
Marcin Andrychowicz, Misha Denil, Sergio Gomez, Matthew W. Hoffman, David Pfau, Tom Schaul, Brendan Shillingford, Nando de Freitas


  Access Paper or Ask Questions

Noisy Activation Functions


Apr 03, 2016
Caglar Gulcehre, Marcin Moczulski, Misha Denil, Yoshua Bengio


  Access Paper or Ask Questions

ACDC: A Structured Efficient Linear Layer


Mar 19, 2016
Marcin Moczulski, Misha Denil, Jeremy Appleyard, Nando de Freitas


  Access Paper or Ask Questions

Deep Fried Convnets


Jul 17, 2015
Zichao Yang, Marcin Moczulski, Misha Denil, Nando de Freitas, Alex Smola, Le Song, Ziyu Wang

* svd experiments included 

  Access Paper or Ask Questions

Extraction of Salient Sentences from Labelled Documents


Feb 28, 2015
Misha Denil, Alban Demiraj, Nando de Freitas

* arXiv admin note: substantial text overlap with arXiv:1406.3830 

  Access Paper or Ask Questions

Deep Multi-Instance Transfer Learning


Dec 10, 2014
Dimitrios Kotzias, Misha Denil, Phil Blunsom, Nando de Freitas


  Access Paper or Ask Questions

Predicting Parameters in Deep Learning


Oct 27, 2014
Misha Denil, Babak Shakibi, Laurent Dinh, Marc'Aurelio Ranzato, Nando de Freitas


  Access Paper or Ask Questions

Modelling, Visualising and Summarising Documents with a Single Convolutional Neural Network


Jun 15, 2014
Misha Denil, Alban Demiraj, Nal Kalchbrenner, Phil Blunsom, Nando de Freitas


  Access Paper or Ask Questions

Distributed Parameter Estimation in Probabilistic Graphical Models


Jun 11, 2014
Yariv Dror Mizrahi, Misha Denil, Nando de Freitas


  Access Paper or Ask Questions

Linear and Parallel Learning of Markov Random Fields


Feb 05, 2014
Yariv Dror Mizrahi, Misha Denil, Nando de Freitas


  Access Paper or Ask Questions

Narrowing the Gap: Random Forests In Theory and In Practice


Oct 04, 2013
Misha Denil, David Matheson, Nando de Freitas

* Under review by the International Conference on Machine Learning (ICML) 2014 

  Access Paper or Ask Questions

Consistency of Online Random Forests


May 08, 2013
Misha Denil, David Matheson, Nando de Freitas

* To appear in Proceedings of the 30th International Conference on Machine Learning, 2013 

  Access Paper or Ask Questions

Recklessly Approximate Sparse Coding


Jan 06, 2013
Misha Denil, Nando de Freitas


  Access Paper or Ask Questions

Learning where to Attend with Deep Architectures for Image Tracking


Sep 16, 2011
Misha Denil, Loris Bazzani, Hugo Larochelle, Nando de Freitas


  Access Paper or Ask Questions

A Characterization of the Combined Effects of Overlap and Imbalance on the SVM Classifier


Sep 16, 2011
Misha Denil, Thomas Trappenberg


  Access Paper or Ask Questions