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Author Information
Ting Chen (Google)
Simon Kornblith (Google Brain)
Kevin Swersky (Google)
Mohammad Norouzi (Google Brain)
Geoffrey E Hinton (Google & University of Toronto)
Geoffrey Hinton received his PhD in Artificial Intelligence from Edinburgh in 1978 and spent five years as a faculty member at Carnegie-Mellon where he pioneered back-propagation, Boltzmann machines and distributed representations of words. In 1987 he became a fellow of the Canadian Institute for Advanced Research and moved to the University of Toronto. In 1998 he founded the Gatsby Computational Neuroscience Unit at University College London, returning to the University of Toronto in 2001. His group at the University of Toronto then used deep learning to change the way speech recognition and object recognition are done. He currently splits his time between the University of Toronto and Google. In 2010 he received the NSERC Herzberg Gold Medal, Canada's top award in Science and Engineering.
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2020 : Policy Panel »
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2019 : Poster Session »
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2019 Poster: Lookahead Optimizer: k steps forward, 1 step back »
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2018 Poster: Discovery of Latent 3D Keypoints via End-to-end Geometric Reasoning »
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2018 Oral: Discovery of Latent 3D Keypoints via End-to-end Geometric Reasoning »
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2018 Poster: Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures »
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2016 Poster: Using Fast Weights to Attend to the Recent Past »
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2016 Oral: Using Fast Weights to Attend to the Recent Past »
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2015 Tutorial: Deep Learning »
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2014 Workshop: Deep Learning and Representation Learning »
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2012 Poster: Hamming Distance Metric Learning »
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2012 Poster: ImageNet Classification with Deep Convolutional Neural Networks »
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2012 Invited Talk: Dropout: A simple and effective way to improve neural networks »
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2010 Talk: A Probabilistic Approach to Data Visualization »
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2010 Oral: Learning to combine foveal glimpses with a third-order Boltzmann machine »
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2010 Poster: Learning to combine foveal glimpses with a third-order Boltzmann machine »
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2010 Poster: Generating more realistic images using gated MRF's »
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2010 Poster: Phone Recognition with the Mean-Covariance Restricted Boltzmann Machine »
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2010 Poster: Gated Softmax Classification »
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2009 Poster: Replicated Softmax: an Undirected Topic Model »
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2009 Poster: 3D Object Recognition with Deep Belief Nets »
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2009 Spotlight: 3D Object Recognition with Deep Belief Nets »
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2009 Invited Talk: Deep Learning with Multiplicative Interactions »
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2009 Poster: Zero-shot Learning with Semantic Output Codes »
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2008 Poster: Using matrices to model symbolic relationship »
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2008 Demonstration: Visualizing NIPS Cooperations using Multiple Maps t-SNE »
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2008 Spotlight: Using matrices to model symbolic relationship »
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2008 Poster: The Recurrent Temporal Restricted Boltzmann Machine »
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2008 Poster: A Scalable Hierarchical Distributed Language Model »
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2008 Poster: Implicit Mixtures of Restricted Boltzmann Machines »
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2008 Poster: Competing RBM density models for classification of fMRI images »
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2007 Tutorial: Deep Belief Nets »
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2007 Poster: Modeling image patches with a directed hierarchy of Markov random fields »
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2006 Poster: Modeling Human Motion Using Binary Latent Variables »
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