Latent variable

Results: 377



#Item
31HONG KONG INSTITUTE FOR MONETARY RESEARCH  RETURN, TRADING VOLUME, AND MARKET DEPTH IN CURRENCY FUTURES MARKETS Ai-ru (Meg) Cheng and Yin-Wong Cheung HKIMR Working Paper No

HONG KONG INSTITUTE FOR MONETARY RESEARCH RETURN, TRADING VOLUME, AND MARKET DEPTH IN CURRENCY FUTURES MARKETS Ai-ru (Meg) Cheng and Yin-Wong Cheung HKIMR Working Paper No

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Source URL: www.hkimr.org

Language: English - Date: 2012-09-25 06:12:36
32Image and Vision Computing–61  Contents lists available at ScienceDirect Image and Vision Computing journal homepage: www.elsevier.com/locate/imavis

Image and Vision Computing–61 Contents lists available at ScienceDirect Image and Vision Computing journal homepage: www.elsevier.com/locate/imavis

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Source URL: ibug.doc.ic.ac.uk

Language: English - Date: 2015-11-12 06:27:17
33Nonparametric Latent Feature Models for Link Prediction Thomas L. Griffiths Psychology and Cognitive Science University of California Berkeley, CA 94720

Nonparametric Latent Feature Models for Link Prediction Thomas L. Griffiths Psychology and Cognitive Science University of California Berkeley, CA 94720

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Source URL: papers.nips.cc

Language: English - Date: 2014-02-24 04:30:07
34Inference on the Effects of Observed Features in Latent Space Models for Networks Zachary Jones Matthew Denny

Inference on the Effects of Observed Features in Latent Space Models for Networks Zachary Jones Matthew Denny

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Source URL: zmjones.com

Language: English - Date: 2016-07-20 11:41:43
353rd Annual Health  Econometrics Workshop

3rd Annual Health Econometrics Workshop

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Source URL: www.healtheconometrics.org

Language: English - Date: 2011-09-23 00:53:50
36An Introduction to Partial Least Squares Regression Randall D. Tobias, SAS Institute Inc., Cary, NC Abstract

An Introduction to Partial Least Squares Regression Randall D. Tobias, SAS Institute Inc., Cary, NC Abstract

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Source URL: www.ats.ucla.edu

Language: English - Date: 2016-08-17 18:18:26
37Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs: Appendices A. Probabilistic Soft Logic  users (i.e., users that are not top users).

Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs: Appendices A. Probabilistic Soft Logic users (i.e., users that are not top users).

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Source URL: stephenbach.net

Language: English - Date: 2015-05-20 14:49:19
    38LEARNING HIDDEN VARIABLES IN PROBABILISTIC GRAPHICAL MODELS T HESIS  SUBMITTED FOR THE DEGREE OF

    LEARNING HIDDEN VARIABLES IN PROBABILISTIC GRAPHICAL MODELS T HESIS SUBMITTED FOR THE DEGREE OF

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    Source URL: www.cs.huji.ac.il

    Language: English - Date: 2015-08-10 08:23:23
    39Language and Document Analysis: Motivating Latent variable Models Wray Buntine National ICT Australia (NICTA)  MLSS, ANU, Jan., 2009

    Language and Document Analysis: Motivating Latent variable Models Wray Buntine National ICT Australia (NICTA) MLSS, ANU, Jan., 2009

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    Source URL: ssll.rsise.anu.edu.au

    Language: English - Date: 2009-02-12 22:12:06
      40Language and Document Analysis: Motivating Latent variable Models Wray Buntine National ICT Australia (NICTA)  MLSS, ANU, Jan., 2009

      Language and Document Analysis: Motivating Latent variable Models Wray Buntine National ICT Australia (NICTA) MLSS, ANU, Jan., 2009

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      Source URL: ssll.rsise.anu.edu.au

      Language: English - Date: 2009-02-12 22:12:11