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1
Bayes nets: A generalized variable elimination algorithm and applications to classification.
Bayes nets: A generalized variable elimination algorithm and applications to classification.
Bayes nets: A generalized variable elimination algorithm and applications to classification.
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Bayes nets: A generalized variable elimination algorithm and applications to classification.

Xiaofang. Lei University of California, Santa Barbara. 2006

Dissertation Abstracts International 67-01B.

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2
Stochastic time series prediction comparison with Markov and support vector machine models.
Stochastic time series prediction comparison with Markov and support vector machine models.
Stochastic time series prediction comparison with Markov and support vector machine models.
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Stochastic time series prediction comparison with Markov and support vector machine models.

Theodore. VanRooy University of Colorado at Boulder. 2006

Masters Abstracts International 45-02.

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3
Sparsity and model selection through convex penalties: Structured selection, covariance selection and some theory.
Sparsity and model selection through convex penalties: Structured selection, covariance selection and some theory.
Sparsity and model selection through convex penalties: Structured selection, covariance selection and some theory.
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Sparsity and model selection through convex penalties: Structured selection, covariance selection and some theory.

Guilherme N. L. Veiga da. Rocha University of California, Berkeley. 2008

Dissertation Abstracts International 69-09B.

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4
Simultaneous variable selection and simultaneous subspace selection for multitask learning.
Simultaneous variable selection and simultaneous subspace selection for multitask learning.
Simultaneous variable selection and simultaneous subspace selection for multitask learning.
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Simultaneous variable selection and simultaneous subspace selection for multitask learning.

Guillaume Romain. Obozinski University of California, Berkeley. 2009

Dissertation Abstracts International 70-10B.

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5
Learning functions on unknown manifolds.
Learning functions on unknown manifolds.
Learning functions on unknown manifolds.
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Learning functions on unknown manifolds.

Xueyuan. Zhou The University of Chicago. Computer Science. 2011

Dissertation Abstracts International 73-04B.

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6
Graphs and Combinatorial Representations of Stochastic Processes.
Graphs and Combinatorial Representations of Stochastic Processes.
Graphs and Combinatorial Representations of Stochastic Processes.
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Graphs and Combinatorial Representations of Stochastic Processes.

Daniel Shaw. Ting University of California, Berkeley. Statistics. 2012

Dissertation Abstracts International 74-07B(E).

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7
Graph Structured Normal Means Inference.
Graph Structured Normal Means Inference.
Graph Structured Normal Means Inference.
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Graph Structured Normal Means Inference.

James. Sharpnack Carnegie Mellon University. 2013

Dissertation Abstracts International 74-12B(E).

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8
Markov Chain Monte Carlo Bayesian predictive framework for artificial Neural Network Committee modeling and simulation.
Markov Chain Monte Carlo Bayesian predictive framework for artificial Neural Network Committee modeling and simulation.
Markov Chain Monte Carlo Bayesian predictive framework for artificial Neural Network Committee modeling and simulation.
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Markov Chain Monte Carlo Bayesian predictive framework for artificial Neural Network Committee modeling and simulation.

Michael S. Goodrich Old Dominion University. 2014

Dissertation Abstracts International 75-08B(E).

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9
Various considerations on performance measures for a classification of ordinal data.
Various considerations on performance measures for a classification of ordinal data.
Various considerations on performance measures for a classification of ordinal data.
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Various considerations on performance measures for a classification of ordinal data.

Denis Barasa. Nyongesa California State University, Long Beach. Mathematics and Statistics. 2016

Masters Abstracts International 55-05(E).

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10
Statistical Learning with Artificial Neural Network Applied To Health and Environmental Data.
Statistical Learning with Artificial Neural Network Applied To Health and Environmental Data.
Statistical Learning with Artificial Neural Network Applied To Health and Environmental Data.
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Statistical Learning with Artificial Neural Network Applied To Health and Environmental Data.

Taysseer. Sharaf ProQuest Information and Learning Co.; University of South Florida. Mathematics and Statistics. 2015

Dissertation Abstracts International 76-09B(E).

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