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Conditional probability
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211	[removed]Machine Learning, Spring 2011: Homework 2 Due: Friday Feb. 4 at 4pm in Sharon Cavlovich’s office (GHC[removed]Instructions There are 3 questions on this assignment. The last question involves coding. Please submit Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2011-01-26 12:02:42 Statistical theory Bayesian statistics Machine learning Naive Bayes classifier Kullback–Leibler divergence Mutual information Conditional entropy Joint probability distribution Normal distribution Statistics Information theory Statistical classification
212	Log-Linear Approach to Discriminative Training NIPS 2008 Workshop “Speech and Language: Learning-based Methods and Systems” Ralf Schl¨ uter, Georg Heigold, and Hermann Ney Add to Reading List Source URL: research.microsoft.com Language: English - Date: 2009-01-03 02:48:23 Discriminative model Generative model Expectation–maximization algorithm Pattern recognition Conditional random field Speech recognition Log-linear model Hidden Markov model Maximum likelihood Statistics Machine learning Probability and statistics
213	Measuring Causal Effects in Partial Mediated Models without Experiments J. Hess In the traditional linear, normal version of the partial mediated model, the above graph corresponds to the equations X=eX, M=aX+eM=aeX+eM, Add to Reading List Source URL: bauer.uh.edu Language: English - Date: 2008-12-02 17:33:37 Information theory Statistical dependence Independence Probability theory Causality Graph Bayesian network Conditional mutual information Graph theory Mathematics Theoretical computer science
214	Conditional Random Fields via Univariate Exponential Families Eunho Yang Department of Computer Science University of Texas at Austin Add to Reading List Source URL: www.cs.utexas.edu Language: English - Date: 2013-11-14 22:48:54 Probability theory Graphical models Regression analysis Theoretical computer science Exponentials Conditional random field Generalized linear model Sufficient statistic Normal distribution Statistics Probability and statistics Probability
215	Declarations of Independence Branden Fitelson and Alan Hájek Abstract: According to orthodox (Kolmogorovian) probability theory, conditional probabilities are by definition certain ratios of unconditional probabilities. Add to Reading List Source URL: fitelson.org Language: English - Date: 2014-06-14 07:25:24 Conditional probability Independence Probability Event Probability space Probability axioms Probability theory Mathematical analysis Mathematics
216	Probabilistic Graphical Models Alessandro Antonucci Cassio P. de Campos Marco Zaffalon Add to Reading List Source URL: ipg.idsia.ch Language: English - Date: 2014-01-03 00:57:12 Credal set Expected value Joint probability distribution Conditioning Independence Function Conditional probability Conditional independence Convex function Probability theory Mathematical analysis Statistics
217	Mixed Graphical Models via Exponential Families Eunho Yang∗ ∗ Yulia Baker† Add to Reading List Source URL: jmlr.org Language: English - Date: 2014-04-14 20:16:23 Graphical models Theoretical computer science Exponentials Statistical models Markov random field Normal distribution Exponential family Gibbs sampling Conditional random field Statistics Probability and statistics Statistical theory
218	Variational Hidden Conditional Random Fields with Coupled Dirichlet Process Mixtures Konstantinos Bousmalis1 , Stefanos Zafeiriou1 , Louis–Philippe Morency2 , Maja Pantic1 , and Zoubin Ghahramani3 1 Add to Reading List Source URL: multicomp.ict.usc.edu Language: English - Date: 2013-07-12 06:30:16 Statistical models Cluster analysis Machine learning Mixture model Markov chain Beta distribution Kullback–Leibler divergence Expectation–maximization algorithm Hidden Markov model Statistics Probability and statistics Markov models
219	Experience matters 1 Experience matters 1 Experience matters 1 Experience matters: Add to Reading List Source URL: www.jonathandnelson.com Language: English - Date: 2009-09-22 20:01:46 Probability theory Statistical theory Probability Kullback–Leibler divergence Bayesian inference Conditional probability Likelihood function Prior probability Random variable Statistics Bayesian statistics Probability and statistics
220	Theory and Applications of Categories, Vol. 29, No. 14, 2014, pp. 389–405. TOWARD CATEGORICAL RISK MEASURE THEORY TAKANORI ADACHI Abstract. We introduce a category that represents varying risk as well as ambiguity. We Add to Reading List Source URL: www.emis.de Language: English - Date: 2014-08-05 12:54:00 Applied mathematics Mathematics Financial economics Conditional expectation Probability space Constructible universe Expected shortfall Dynamic risk measure Expected value Financial risk Mathematical finance Probability theory

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