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Yoshua Bengio

Researcher at Université de Montréal

Publications -  1146
Citations -  534376

Yoshua Bengio is an academic researcher from Université de Montréal. The author has contributed to research in topics: Artificial neural network & Deep learning. The author has an hindex of 202, co-authored 1033 publications receiving 420313 citations. Previous affiliations of Yoshua Bengio include McGill University & Centre de Recherches Mathématiques.

Papers
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Generative adversarial networks

TL;DR: A generative adversarial networks algorithm designed to solve the generative modeling problem and its applications in medicine, education and robotics are studied.
Posted Content

Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1

TL;DR: A binary matrix multiplication GPU kernel is written with which it is possible to run the MNIST BNN 7 times faster than with an unoptimized GPU kernel, without suffering any loss in classification accuracy.
Proceedings Article

Word Representations: A Simple and General Method for Semi-Supervised Learning

TL;DR: This work evaluates Brown clusters, Collobert and Weston (2008) embeddings, and HLBL (Mnih & Hinton, 2009) embeds of words on both NER and chunking, and finds that each of the three word representations improves the accuracy of these baselines.
Posted Content

Theano: A Python framework for fast computation of mathematical expressions

Rami Al-Rfou, +111 more
TL;DR: The performance of Theano is compared against Torch7 and TensorFlow on several machine learning models and recently-introduced functionalities and improvements are discussed.
Posted Content

Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

TL;DR: This work considers a small-scale version of {\em conditional computation}, where sparse stochastic units form a distributed representation of gaters that can turn off in combinatorially many ways large chunks of the computation performed in the rest of the neural network.