Semi-supervised learning

Results: 318



#Item
11Real-World Semi-Supervised Learning of POS-Taggers for Low-Resource Languages Dan Garrette1 Jason Mielens2

Real-World Semi-Supervised Learning of POS-Taggers for Low-Resource Languages Dan Garrette1 Jason Mielens2

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Source URL: www.aclweb.org

Language: English - Date: 2013-07-25 09:24:47
    12Semi-Supervised Learning of a Pronunciation Dictionary from Disjoint Phonemic Transcripts and Text Takahiro Shinozaki1 , Shinji Watanabe2 , Daichi Mochihashi3 , Graham Neubig4 1 2

    Semi-Supervised Learning of a Pronunciation Dictionary from Disjoint Phonemic Transcripts and Text Takahiro Shinozaki1 , Shinji Watanabe2 , Daichi Mochihashi3 , Graham Neubig4 1 2

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    Source URL: www.phontron.com

    Language: English - Date: 2017-09-01 06:48:26
      13Semi-supervised Learning Piyush Rai Machine Learning (CS771A) Oct 28, 2016 Machine Learning (CS771A)

      Semi-supervised Learning Piyush Rai Machine Learning (CS771A) Oct 28, 2016 Machine Learning (CS771A)

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      Source URL: cse.iitk.ac.in

      - Date: 2016-10-28 10:35:16
        14Semi-supervised Learning of Compact Document Representations with Deep Networks Marc’Aurelio Ranzato Courant Institute, New York University, 719 Broadway 12th fl., New York NY 10003, USA

        Semi-supervised Learning of Compact Document Representations with Deep Networks Marc’Aurelio Ranzato Courant Institute, New York University, 719 Broadway 12th fl., New York NY 10003, USA

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        Source URL: www.cs.nyu.edu

        - Date: 2008-05-19 11:10:05
          15ICG CVPR 2010 Tutorial Semi-Supervised Learning in Vision A, Saffari, Ch. Leistner, H. Bischof

          ICG CVPR 2010 Tutorial Semi-Supervised Learning in Vision A, Saffari, Ch. Leistner, H. Bischof

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          Source URL: www.ymer.org

          - Date: 2010-06-17 16:33:36
            16Kernel Conditional Random Fields: Representation, Clique Selection, and Semi-Supervised Learning John Lafferty, Yan Liu and Xiaojin Zhu February 5, 2004 CMU-CS

            Kernel Conditional Random Fields: Representation, Clique Selection, and Semi-Supervised Learning John Lafferty, Yan Liu and Xiaojin Zhu February 5, 2004 CMU-CS

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            Source URL: www.aladdin.cs.cmu.edu

            - Date: 2010-11-17 10:54:43
              17Wasserstein Propagation for Semi-Supervised Learning Justin Solomon JUSTIN . SOLOMON @ STANFORD . EDU Raif M. Rustamov RUSTAMOV @ STANFORD . EDU

              Wasserstein Propagation for Semi-Supervised Learning Justin Solomon JUSTIN . SOLOMON @ STANFORD . EDU Raif M. Rustamov RUSTAMOV @ STANFORD . EDU

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              Source URL: jmlr.org

              - Date: 2014-02-16 19:30:21
                18Poster: (Semi)-Supervised Machine Learning Approaches for Network Security in High-Dimensional Network Data Pedro Casas (1)∗ , Alessandro D’Alconzo (1), Giuseppe Settanni (1), Pierdomenico Fiadino (2), Florian Skopik

                Poster: (Semi)-Supervised Machine Learning Approaches for Network Security in High-Dimensional Network Data Pedro Casas (1)∗ , Alessandro D’Alconzo (1), Giuseppe Settanni (1), Pierdomenico Fiadino (2), Florian Skopik

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                Source URL: www.flosko.at

                - Date: 2016-10-01 10:24:48
                  19Online Learning of Deep Hybrid Architectures for Semi-Supervised Categorization Alexander G. Ororbia II, David Reitter, Jian Wu, and C. Lee Giles College of Information Sciences and Technology, The Pennsylvania State Uni

                  Online Learning of Deep Hybrid Architectures for Semi-Supervised Categorization Alexander G. Ororbia II, David Reitter, Jian Wu, and C. Lee Giles College of Information Sciences and Technology, The Pennsylvania State Uni

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                  Source URL: www.david-reitter.com

                  - Date: 2016-12-01 11:37:10