Deep learning

Results: 859



#Item
111

SHIKHAR SHARMA Research SDE II, Microsoft Research http://www.shikharsharma.com/ RESEARCH INTERESTS • Deep Learning

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Source URL: www.shikharsharma.com

- Date: 2018-03-01 11:22:22
    112

    arXiv:1706.07567v1 [cs.CV] 23 JunSampling Matters in Deep Embedding Learning Chao-Yuan Wu∗ UT Austin

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    Source URL: www.philkr.net

    - Date: 2017-10-06 12:46:13
      113

      JMLR: Workshop and Conference Proceedings 80:1–17, 2017 ACML 2017 Recognizing Art Style Automatically in painting with deep learning

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      Source URL: www.lamsade.dauphine.fr

      - Date: 2017-10-26 09:45:26
        114

        Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow Kanit Wongsuphasawat, Daniel Smilkov, James Wexler, Jimbo Wilson, ´ Doug Fritz, Dilip Krishnan, Fernanda B. Viegas, ´ Dandelion Mane,

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        Source URL: idl.cs.washington.edu

          115

          Deep Learning, Special-purpose hardware, and some hard problems Cliff Young, CCC Panel on AI and Amplifying Human Abilities 23 October 2017

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          Source URL: cra.org

          - Date: 2017-10-23 14:24:12
            116

            Two Ideas For Structured Data: ● Reward augmented maximum likelihood ● Order matters Samy Bengio, and the Brain team Reward augmented maximum likelihood

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            Source URL: berkeley-deep-learning.github.io

            - Date: 2017-04-30 17:03:03
              117

              Learning Deep Object Detectors from 3D Models Xingchao Peng, Baochen Sun, Karim Ali, Kate Saenko University of Massachusetts Lowell arXiv:1412.7122v4 [cs.CV] 12 Oct 2015

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              Source URL: cs-people.bu.edu

              - Date: 2017-12-15 00:58:34
                118

                Learning to Track at 100 FPS with Deep Regression Networks David Held, Sebastian Thrun, Silvio Savarese Department of Computer Science Stanford University {davheld,thrun,ssilvio}@cs.stanford.edu

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                Source URL: davheld.github.io

                - Date: 2017-12-05 20:18:02
                  119

                  Installing and Running Caffe2 Caffe2 is a deep learning framework that supports both convolutional and recurrent networks Frameworks Dependencies Caffe2 requires protobuf, atlas, glog, gtest, limdb, leveldb, snappy, Open

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                  Source URL: www.cadnetwork.de

                  - Date: 2017-07-21 09:07:19
                    120

                    A HYBRID DSP/DEEP LEARNING APPROACH TO REAL-TIME FULL-BAND SPEECH ENHANCEMENT Jean-Marc Valin Mozilla Corporation Mountain View, CA, USA

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                    Source URL: jmvalin.ca

                    - Date: 2017-10-28 02:13:06
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