Bregman

Results: 93



#Item
51STAT 538 Lecture 2 Conjugate Function, Bregman Divergences, Concepts of Information Theory c 
Marina Meil˘a

STAT 538 Lecture 2 Conjugate Function, Bregman Divergences, Concepts of Information Theory c Marina Meil˘a

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Source URL: www.stat.washington.edu

Language: English - Date: 2015-01-13 22:08:39
52Loss Functions Robert C. Williamson Abstract Vapnik described the “three main learning problems” of pattern recognition, regression estimation and density estimation. These are defined in terms of the loss functions

Loss Functions Robert C. Williamson Abstract Vapnik described the “three main learning problems” of pattern recognition, regression estimation and density estimation. These are defined in terms of the loss functions

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Source URL: users.cecs.anu.edu.au

Language: English - Date: 2013-04-06 02:21:38
53Convex Relaxations of Bregman Divergence Clustering  Hao Cheng Department of Computing Science  Xinhua Zhang

Convex Relaxations of Bregman Divergence Clustering Hao Cheng Department of Computing Science Xinhua Zhang

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Source URL: users.cecs.anu.edu.au

Language: English - Date: 2013-07-06 17:47:25
54Journal of Machine Learning Research ? ([removed]Submitted 8/09; Published ??/?? Information, Divergence and Risk for Binary Experiments Mark D. Reid

Journal of Machine Learning Research ? ([removed]Submitted 8/09; Published ??/?? Information, Divergence and Risk for Binary Experiments Mark D. Reid

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Source URL: users.cecs.anu.edu.au

Language: English - Date: 2009-08-23 23:03:10
55Accelerated Training of Max-Margin Markov Networks with Kernels Xinhua Zhang∗ Department of Computing Science, University of Alberta, Edmonton, AB T6G2E8, Canada  Ankan Saha

Accelerated Training of Max-Margin Markov Networks with Kernels Xinhua Zhang∗ Department of Computing Science, University of Alberta, Edmonton, AB T6G2E8, Canada Ankan Saha

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Source URL: users.cecs.anu.edu.au

Language: English - Date: 2013-02-25 19:29:17
56Bregman Divergence and Mirror Descent  1 Bregman Divergence

Bregman Divergence and Mirror Descent 1 Bregman Divergence

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Source URL: users.cecs.anu.edu.au

Language: English - Date: 2013-12-27 03:32:34
57Regularizers versus Losses for Nonlinear Dimensionality Reduction

Regularizers versus Losses for Nonlinear Dimensionality Reduction

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Source URL: users.cecs.anu.edu.au

Language: English - Date: 2012-06-02 22:35:08
58PQBSBKMFKHBOLK  ALBERT BREGMAN Albert Bregman, my mentor in cognitive psychology, was hardly my role model as a teacher. I became a modern lecturer-entertainer, with bullet points, borscht-belt humor and audiovisual ra

PQBSBKMFKHBOLK ALBERT BREGMAN Albert Bregman, my mentor in cognitive psychology, was hardly my role model as a teacher. I became a modern lecturer-entertainer, with bullet points, borscht-belt humor and audiovisual ra

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Source URL: pinker.wjh.harvard.edu

Language: English - Date: 2011-04-07 12:18:08
59JMLR: Workshop and Conference Proceedings vol[removed]–[removed]25th Annual Conference on Learning Theory A Characterization of Scoring Rules for Linear Properties JABER @ SEAS . UPENN . EDU ∗

JMLR: Workshop and Conference Proceedings vol[removed]–[removed]25th Annual Conference on Learning Theory A Characterization of Scoring Rules for Linear Properties JABER @ SEAS . UPENN . EDU ∗

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Source URL: jmlr.csail.mit.edu

Language: English - Date: 2012-06-17 06:50:53
60Strictly Proper Scoring Rules, Prediction, and Estimation Tilmann G NEITING and Adrian E. R AFTERY Scoring rules assess the quality of probabilistic forecasts, by assigning a numerical score based on the predictive distr

Strictly Proper Scoring Rules, Prediction, and Estimation Tilmann G NEITING and Adrian E. R AFTERY Scoring rules assess the quality of probabilistic forecasts, by assigning a numerical score based on the predictive distr

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Source URL: www.csss.washington.edu

Language: English - Date: 2008-05-20 22:04:51