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Statistical learning theory
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261	Hyperparameter Learning for Graph Based Semi-supervised Learning Algorithms Xinhua Zhang∗ Statistical Machine Learning Program National ICT Australia, Canberra, Australia and CSL, RSISE, ANU, Canberra, Australia Add to Reading List Source URL: www.comp.nus.edu.sg Language: English - Date: 2007-01-22 02:27:21 Theoretical computer science Semi-supervised learning Supervised learning Graph Tree Flow network Active learning Graph theory Machine learning Mathematics
262	LATENT COINCIDENCE ANALYSIS: A HIDDEN VARIABLE MODEL FOR DISTANCE METRIC LEARNING Matthew Der and Lawrence K. Saul, University of California, San Diego 1 INTRODUCTION Add to Reading List Source URL: cseweb.ucsd.edu Language: English - Date: 2012-12-11 16:44:37 Statistical models K-nearest neighbor algorithm Mixture model Estimation theory Expectation–maximization algorithm Statistics Machine learning Artificial intelligence
263	Copyright © 2011 by Statistical Innovations Inc. All rights reserved. (version: Tutorial 4: Obtaining Predictions from a 2-class Regression in CORExpress® Dataset for running CCR Linear Regression (CCR.lm Add to Reading List Source URL: www.statisticalinnovations.com Language: English - Date: 2012-02-08 14:34:21 Estimation theory Parametric statistics Machine learning Linear regression Cross-validation SPSS Ordinary least squares GUI widget Statistics Regression analysis Econometrics
264	Learning Module Statistics 2 Some general principles: measures of uncertainty and small number issues Add to Reading List Source URL: www.wmpho.org.uk Language: English - Date: 2010-03-01 05:57:37 Robust statistics Data analysis Statistical theory Outlier Average Elephant Errors and residuals in statistics Sample mean and sample covariance Arithmetic mean Statistics Summary statistics Means
265	Predicting Online Media Effectiveness Based on Smile Responses Gathered Over the Internet Daniel McDuff, Rana el Kaliouby, David Demirdjian and Rosalind Picard I. I NTRODUCTION The face has been shown to communicate disc Add to Reading List Source URL: affect.media.mit.edu Language: English - Date: 2013-04-30 11:10:54 Machine learning Data mining Detection theory Receiver operating characteristic Naive Bayes classifier Affective computing Smile Gain Affect Statistics Statistical classification Feeling
266	Learning Evolving and Emerging Topics in Social Media: A Dynamic NMF approach with Temporal Regularization Ankan Saha∗ Vikas Sindhwani Add to Reading List Source URL: people.cs.uchicago.edu Language: English - Date: 2012-01-12 12:52:28 Statistical natural language processing Linear algebra Matrix theory Multivariate statistics Numerical linear algebra Non-negative matrix factorization Online NMF Topic model Dynamic topic model Algebra Mathematics Statistics
267	2015 Exam 4 Syllabus Construction and Evaluation of Actuarial Models Exam The syllabus for this exam is defined in the form of learning objectives that set forth, usually in broad terms, what the candidate should be able Add to Reading List Source URL: www.casact.org Language: English - Date: 2014-10-09 09:59:36 Estimation theory Statistical inference Actuarial science Statistical theory Actuary Institute and Faculty of Actuaries Institute of Actuaries Faculty of Actuaries Maximum likelihood Statistics Insurance Mathematical sciences
268	Learning Bayesian Network Structure from Correlation-Immune Data Eric Lantz Computer Sciences Dept. University of Wisconsin-Madison Add to Reading List Source URL: pages.cs.wisc.edu Language: English - Date: 2007-08-15 11:57:24 Probability and statistics Measurement Bayesian network Networks Probability theory Mutual information Correlation and dependence Machine learning Random variable Statistics Statistical models Graphical models
269	PDF Document Add to Reading List Source URL: www.mth.kcl.ac.uk Language: English - Date: 2014-10-17 06:59:26 Machine learning Statistical theory Cross-validation Model selection Expectation–maximization algorithm Maximum likelihood Naive Bayes classifier Validation Linear discriminant analysis Statistics Estimation theory Statistical classification
270	PDF Document Add to Reading List Source URL: papers.nips.cc Language: English - Date: 2014-11-26 14:29:24 Machine learning Estimation theory Statistical theory Expectation–maximization algorithm Bayesian network Gibbs sampling Perceptron Kullback–Leibler divergence Mixture model Statistics Statistical models Neural networks

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