Multinomial

Results: 358



#Item
31A Bayesian Framework for Modeling Human Evaluations Himabindu Lakkaraju∗ Jure Leskovec∗  Abstract

A Bayesian Framework for Modeling Human Evaluations Himabindu Lakkaraju∗ Jure Leskovec∗ Abstract

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Source URL: cs.stanford.edu

Language: English - Date: 2015-01-29 11:19:57
32GEE for Multinomial Responses Using a Local Odds Ratios Parameterization

GEE for Multinomial Responses Using a Local Odds Ratios Parameterization

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Source URL: www.stat.ufl.edu

Language: English - Date: 2015-08-01 13:07:36
    33Topic Models Conditioned on Arbitrary Features with Dirichlet-multinomial Regression David Mimno Computer Science Dept. University of Massachusetts, Amherst

    Topic Models Conditioned on Arbitrary Features with Dirichlet-multinomial Regression David Mimno Computer Science Dept. University of Massachusetts, Amherst

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    Source URL: uai2008.cs.helsinki.fi

    Language: English - Date: 2008-05-16 11:55:56
      34An application of the Constrained Multinomial Logit (CMNL) for modelling dominated choice alternatives Francisco Martínez, University of Chile Ennio Cascetta, Francesca Pagliara, University of Naples Michel Bierlaire, T

      An application of the Constrained Multinomial Logit (CMNL) for modelling dominated choice alternatives Francisco Martínez, University of Chile Ennio Cascetta, Francesca Pagliara, University of Naples Michel Bierlaire, T

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      Source URL: www.strc.ch

      Language: English - Date: 2008-11-24 07:42:20
      35Modeling Documents with a Deep Boltzmann Machine  Nitish Srivastava Ruslan Salakhutdinov Geoffrey Hinton

      Modeling Documents with a Deep Boltzmann Machine Nitish Srivastava Ruslan Salakhutdinov Geoffrey Hinton

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      Source URL: www.cs.toronto.edu

      Language: English - Date: 2015-07-13 11:35:04
      36Website Fingerprinting Attacking Popular Privacy Enhancing Technologies with the Multinomial Naïve-Bayes Classifier Dominik Herrmann, Hannes Federrath University of Regensburg, Germany

      Website Fingerprinting Attacking Popular Privacy Enhancing Technologies with the Multinomial Naïve-Bayes Classifier Dominik Herrmann, Hannes Federrath University of Regensburg, Germany

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      Source URL: digitalpiglet.org

      Language: English - Date: 2009-11-27 08:33:02
      37Microsoft Word - Scagnolari_Maggi_2010.docx

      Microsoft Word - Scagnolari_Maggi_2010.docx

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      Source URL: www.strc.ch

      Language: English - Date: 2010-08-28 08:10:44
      38Object-fine choice models for long-term decisions: which level of granularity is necessary? A review of literature VAN EGGERMOND Michael A.B.* , ERATH Alexander* , and AXHAUSEN Kay W.** *

      Object-fine choice models for long-term decisions: which level of granularity is necessary? A review of literature VAN EGGERMOND Michael A.B.* , ERATH Alexander* , and AXHAUSEN Kay W.** *

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      Source URL: www.strc.ch

      Language: English - Date: 2012-05-16 11:55:24
      39Discrete mixtures of GEV models  Stephane Hess, Imperial College London & RAND Europe Michel Bierlaire, EPFL John W. Polak, Imperial College London Conference paper STRC 2005

      Discrete mixtures of GEV models Stephane Hess, Imperial College London & RAND Europe Michel Bierlaire, EPFL John W. Polak, Imperial College London Conference paper STRC 2005

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      Source URL: www.strc.ch

      Language: English - Date: 2008-12-12 11:45:48
      40Parametric order constraints in multinomial processing tree models: An extension of Knapp and Batchelder (2004)

      Parametric order constraints in multinomial processing tree models: An extension of Knapp and Batchelder (2004)

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      Source URL: singmann.org

      Language: English