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Bayesian network
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951	92 CHAPTER 4. PREDICTIVE MODELS defines a probability space for which (X, E, P ) is a Bayesian network. Furthermore, P (Xi \|C(Xi)) is either 0 or fi (Xi ). Here C(Xi ) denotes the parents (or direct causes) of Xi . Add to Reading List Source URL: datamining.anu.edu.au Language: English - Date: 2011-05-31 01:27:15 Mean squared error Variance Errors and residuals in statistics Gauss–Markov theorem Bias of an estimator Multivariate adaptive regression splines Residual sum of squares Linear regression Ordinary least squares Statistics Regression analysis Least squares
952	Table of Contents 1. Archipelago: Nonparametric Bayesian Semi-Supervised Learning ........................................................ 1 Ryan Adams and Zoubin Ghahramani 2. Tractable Nonparametric Bayesian Inference Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2009-06-20 15:37:14 Networks Bayesian statistics Probability theory Supervised learning Bayesian network Structured prediction Regularization Linear classifier Unsupervised learning Statistics Machine learning Graphical models
953	Computational Aspects of Bayesian Partition Models Mikko Koivisto [removed] HIIT Basic Research Unit, Dept. of Computer Science, University of Helsinki, FIN[removed]Helsinki, Finland Kismat Sood Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:15:52 Model selection Bayesian network Networks Bayesian inference Regression analysis Algorithm Feature selection Partition Variational Bayesian methods Statistics Bayesian statistics Statistical models
954	Discriminative versus Generative Parameter and Structure Learning of Bayesian Network Classifiers Franz Pernkopf PERNKOPF @ TUGRAZ . AT Department of Electrical Engineering, Graz University of Technology, Inffeldgasse 16 Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:14:47 Statistical models Statistical classification Naive Bayes classifier Generative model Bayesian network Pattern recognition Discriminative model Random naive Bayes Linear classifier Statistics Machine learning Bayesian statistics
955	Factored Conditional Restricted Boltzmann Machines for Modeling Motion Style Graham W. Taylor GWTAYLOR @ CS . TORONTO . EDU Geoffrey E. Hinton Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2009-05-18 12:17:00 Probability and statistics Neural networks Machine learning Boltzmann machine Generative model Graphical model Hidden Markov model Bayesian network Ludwig Boltzmann Statistical models Statistics Bayesian statistics
956	Table of Contents Preface .................................................................................................................................................................... xiii Organization ........... Add to Reading List Source URL: www.icml2010.org Language: English - Date: 2010-07-25 05:16:19 Supervised learning Cluster analysis Bayesian network Regression analysis Reinforcement learning Hidden Markov model Michael I. Jordan Statistical classification Semi-supervised learning Statistics Machine learning Artificial intelligence
957	Association Search in Semantic Web: Search + Inference Liang Bangyong Tang Jie Li Juanzi Add to Reading List Source URL: www2005.org Language: English - Date: 2005-04-05 10:32:01 Statistics Knowledge Internet search engines Bayesian network Networks Inference Semantic search Knowledge representation and reasoning Reasoning Semantic Web Logic
958	Recovering Temporally Rewiring Networks: A Model-based Approach Fan Guo [removed] Steve Hanneke Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:25:14 Markov models Bioinformatics Evolving networks Bayesian network Exponential random graph models Gene regulatory network Markov chain Topology Expectation–maximization algorithm Statistics Networks Network theory
959	Microsoft Word - Bayesian Inference for NASA Risk and Reliability Analysis - Final 2009.doc Add to Reading List Source URL: www.hq.nasa.gov Language: English - Date: 2010-12-29 14:19:16 Statistical theory Markov models Bayesian inference Bayesian linear regression Markov chain Monte Carlo Credible interval Estimation theory Markov chain Bayesian network Statistics Bayesian statistics Statistical inference
960	Invited Applications Paper FAB-MAP: Appearance-Based Place Recognition and Mapping using a Learned Visual Vocabulary Model Mark Cummins Add to Reading List Source URL: www.icml2010.org Language: English - Date: 2010-06-13 09:06:58 Simultaneous localization and mapping Robotic mapping Kalman filter Pattern recognition Naive Bayes classifier Bayesian network Statistics Bayesian statistics Robot navigation

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