Geoffrey Canada

Results: 43



#Item
1

Learning to Detect Roads in High-Resolution Aerial Images Volodymyr Mnih and Geoffrey E. Hinton Department of Computer Science, University of Toronto, 6 King’s College Rd., Toronto, Ontario, M5S 3G4, Canada

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Source URL: www.cs.toronto.edu

Language: English - Date: 2010-07-08 15:47:50
    2

    Wormholes Improve Contrastive Divergence Geoffrey Hinton, Max Welling Department of Computer Science, University of Toronto 10 King’s College Road, Toronto, M5S 3G5 Canada {hinton,welling}@cs.toronto.edu

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    Source URL: www.cs.toronto.edu

    - Date: 2004-12-05 12:56:59
      3

      Generating Text with Recurrent Neural Networks Ilya Sutskever James Martens Geoffrey Hinton University of Toronto, 6 King’s College Rd., Toronto, ON M5S 3G4 CANADA

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      Source URL: machinelearning.wustl.edu

      Language: English - Date: 2013-03-25 14:58:55
        4

        LEARNING A BETTER REPRESENTATION OF SPEECH SOUND WAVES USING RESTRICTED BOLTZMANN MACHINES Navdeep Jaitly, Geoffrey Hinton Department of Computer Science, University of Toronto, Toronto, M5S 3G4, Canada ABSTRACT State of

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        Source URL: www.cs.toronto.edu

        Language: English - Date: 2011-03-01 16:21:12
          5

          News Relase For Immediate Release The Government of Canada and the Federation of Newfoundland Indians Announce Appointment of Geoffrey Brown as Chief Appeal Master to the Qalipu Enrolment Process

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          Source URL: qalipu.ca

          Language: English - Date: 2015-07-31 07:11:45
            6

            FOR IMMEDIATE RELEASE CONTACT: Taryn Roeder Houghton Mifflin Harcourtphone) “This American Life contributor Tough (Whatever It Takes: Geoffrey Canada’s Quest to

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            Source URL: www.paultough.com

            Language: English - Date: 2012-08-11 14:07:06
              7Artificial neural networks / Restricted Boltzmann machine / Boltzmann machine / Autoencoder / Backpropagation / Feedforward neural network / Generative model / Connectionism / Supervised learning / Graphical model / Machine learning / Hidden Markov model

              Where do features come from? Geoffrey Hinton Department of Computer Science, University of Toronto 6 King’s College Rd, M5S 3G4, Canada February 18, 2013

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              Source URL: www.cs.toronto.edu

              Language: English - Date: 2015-07-13 11:50:55
              8

              3D Object Recognition with Deep Belief Nets Vinod Nair and Geoffrey E. Hinton Department of Computer Science, University of Toronto 10 King’s College Road, Toronto, M5S 3G5 Canada {vnair,hinton}@cs.toronto.edu

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              Source URL: www.cs.toronto.edu

              Language: English - Date: 2010-06-15 13:03:51
                9

                1 CHAPTER 6 – BORDER SECURITY, TRADE AND TRAVEL FACILITATION Geoffrey Hale and Christina Marcotte In Monica Gattinger and Geoffrey Hale, eds. (forthcoming), Borders and Bridges: Navigating Canada’s Policy Relations

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                Source URL: people.uleth.ca

                - Date: 2009-04-04 16:36:26
                  10

                  Inferring Motor Programs from Images of Handwritten Digits Geoffrey Hinton and Vinod Nair Department of Computer Science, University of Toronto 10 King’s College Road, Toronto, M5S 3G5 Canada

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                  Source URL: www.cs.toronto.edu

                  Language: English - Date: 2006-02-24 13:05:17
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