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Statistical theory
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791	R Last Edited: Module name: R 2. Scope: a. This module covers use of the R language for performing the statistical analysis needed for Add to Reading List Source URL: curric.dlib.vt.edu Language: English - Date: 2011-01-19 20:55:58 Matrix theory Linear algebra Numerical linear algebra Natural language processing Singular value decomposition Latent semantic analysis Matrix Eigenvalues and eigenvectors Diagonal matrix Eigendecomposition of a matrix Document-term matrix Determinant
792	The Complete Mixability and Convex Minimization Problems with Monotone Marginal Densities Bin Wang∗ and Ruodu Wang† May 9, 2011 Abstract Add to Reading List Source URL: sas.uwaterloo.ca Language: English - Date: 2011-05-09 10:28:41 Mathematical analysis Statistics Probability Probability distributions Statistical theory Binomial distribution Distribution Expected value Completeness
793	The Annals of Applied Statistics 2014, Vol. 8, No. 2, 1256–1280 DOI: AOAS739 © Institute of Mathematical Statistics, 2014 PROBABILITY AGGREGATION IN TIME-SERIES: DYNAMIC Add to Reading List Source URL: www-stat.wharton.upenn.edu Language: English - Date: 2014-07-06 15:12:10 Probability Statistics Statistical theory Bayesian statistics Sampling Survey methodology Kalman filter Calibrated probability assessment Probability distribution Brier score Mathematical statistics Prior probability
794	Markov Chain Monte Carlo and Variational Inference: Bridging the Gap Tim Salimans Algoritmica TIM @ ALGORITMICA . NL Add to Reading List Source URL: jmlr.org Language: English - Date: 2015-09-16 19:38:47 Statistics Statistical theory Probability Markov models Computational statistics Bayesian statistics Monte Carlo methods Monte Carlo software Variational Bayesian methods Bayesian network Markov chain Gibbs sampling
795	journalof Journal of Statistical Planning and InferenceELSEVIER Add to Reading List Source URL: www.ntu.edu.sg Language: English - Date: 2014-02-28 04:33:22 Fourier analysis Multiplier Difference set Divisor Sheaf theory Binary operations Sheaf of modules Convolution
796	JMLR: Workshop and Conference Proceedings vol 40:1–21, 2015 Learning and inference in the presence of corrupted inputs Uriel Feige URIEL . FEIGE @ WEIZMANN . AC . IL Add to Reading List Source URL: jmlr.org Language: English - Date: 2015-07-20 20:08:36 Machine learning Learning Stability Linear programming Function Statistical learning theory Matching
797	On Agreement and Learning∗ Elchanan Mossel†, Allan Sly‡and Omer Tamuz§ arXiv:1207.5895v1 [math.ST] 25 JulJuly 26, 2012 Add to Reading List Source URL: people.hss.caltech.edu Language: English - Date: 2012-07-27 05:59:55 Game theory Bayesian statistics Statistical inference Statistical theory Probability and statistics Bayesian game Bayesian inference Posterior probability Probability Conditional independence Common knowledge Bayesian network
798	Blind restoration of blurred photographs via AR modelling and MCMC Add to Reading List Source URL: decsai.ugr.es Language: English - Date: 2008-11-01 16:02:34 Mathematical analysis Statistics Mathematics Functional analysis Image processing Signal processing Fourier analysis Statistical theory Convolution Maximum likelihood estimation Distribution Normal distribution
799	How do you know that? Sensitivity to statistical dependency in social learning Andrew Whalen () Daphna Buchsbaum () Thomas L. Griffiths (tom ) Department of Psyc Add to Reading List Source URL: cocosci.berkeley.edu Language: English - Date: 2013-05-02 18:42:13 Statistics Statistical theory Statistical inference Information Knowledge Probability and statistics Bayesian statistics Behavioral finance Information cascade Informant Probability Bayesian inference
800	Generative probabilistic models extend the scope of inferential structure determination Add to Reading List Source URL: people.binf.ku.dk Language: English - Date: 2012-01-24 06:25:17 Statistics Statistical theory Protein methods Protein structure Bioinformatics Markov chain Monte Carlo Gibbs sampling Root-mean-square deviation Monte Carlo method Bayesian inference Structure validation Global optimization

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