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Gradient Starvation: A Learning Proclivity in Neural Networks

Nov 23, 2020
Mohammad Pezeshki, SĂ©kou-Oumar Kaba, Yoshua Bengio, Aaron Courville, Doina Precup, Guillaume Lajoie


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On the Learning Dynamics of Deep Neural Networks

Sep 18, 2018
Remi Tachet des Combes, Mohammad Pezeshki, Samira Shabanian, Aaron Courville, Yoshua Bengio

* 19 pages, 7 figures 

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Negative Momentum for Improved Game Dynamics

Jul 12, 2018
Gauthier Gidel, Reyhane Askari Hemmat, Mohammad Pezeshki, Gabriel Huang, Remi Lepriol, Simon Lacoste-Julien, Ioannis Mitliagkas


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Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations

Sep 22, 2017
David Krueger, Tegan Maharaj, János Kramár, Mohammad Pezeshki, Nicolas Ballas, Nan Rosemary Ke, Anirudh Goyal, Yoshua Bengio, Aaron Courville, Chris Pal

* David Krueger and Tegan Maharaj contributed equally to this work 

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Towards End-to-End Speech Recognition with Deep Convolutional Neural Networks

Jan 10, 2017
Ying Zhang, Mohammad Pezeshki, Philemon Brakel, Saizheng Zhang, Cesar Laurent Yoshua Bengio, Aaron Courville


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Deconstructing the Ladder Network Architecture

May 24, 2016
Mohammad Pezeshki, Linxi Fan, Philemon Brakel, Aaron Courville, Yoshua Bengio

* Proceedings of the 33 rd International Conference on Machine Learning, New York, NY, USA, 2016 

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Theano: A Python framework for fast computation of mathematical expressions

May 09, 2016
The Theano Development Team, Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermueller, Dzmitry Bahdanau, Nicolas Ballas, Frédéric Bastien, Justin Bayer, Anatoly Belikov, Alexander Belopolsky, Yoshua Bengio, Arnaud Bergeron, James Bergstra, Valentin Bisson, Josh Bleecher Snyder, Nicolas Bouchard, Nicolas Boulanger-Lewandowski, Xavier Bouthillier, Alexandre de Brébisson, Olivier Breuleux, Pierre-Luc Carrier, Kyunghyun Cho, Jan Chorowski, Paul Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Mélanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian Goodfellow, Matt Graham, Caglar Gulcehre, Philippe Hamel, Iban Harlouchet, Jean-Philippe Heng, Balázs Hidasi, Sina Honari, Arjun Jain, Sébastien Jean, Kai Jia, Mikhail Korobov, Vivek Kulkarni, Alex Lamb, Pascal Lamblin, Eric Larsen, César Laurent, Sean Lee, Simon Lefrancois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert T. McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher Pal, Razvan Pascanu, Mohammad Pezeshki, Colin Raffel, Daniel Renshaw, Matthew Rocklin, Adriana Romero, Markus Roth, Peter Sadowski, John Salvatier, François Savard, Jan Schlüter, John Schulman, Gabriel Schwartz, Iulian Vlad Serban, Dmitriy Serdyuk, Samira Shabanian, Étienne Simon, Sigurd Spieckermann, S. Ramana Subramanyam, Jakub Sygnowski, Jérémie Tanguay, Gijs van Tulder, Joseph Turian, Sebastian Urban, Pascal Vincent, Francesco Visin, Harm de Vries, David Warde-Farley, Dustin J. Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, Ying Zhang

* 19 pages, 5 figures 

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Sequence Modeling using Gated Recurrent Neural Networks

Jan 01, 2015
Mohammad Pezeshki


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Distinction between features extracted using deep belief networks

Jan 02, 2014
Mohammad Pezeshki, Sajjad Gholami, Ahmad Nickabadi

* 4 pages, 4 figures, ICLR 2014 workshop track 

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Deep Belief Networks for Image Denoising

Jan 02, 2014
Mohammad Ali Keyvanrad, Mohammad Pezeshki, Mohammad Ali Homayounpour

* ICLR 2014 Conference track 

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