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Natural exponential family
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1	Ann Inst Stat Math:469–490 DOIs10463Second-order asymptotic comparison of the MLE and MCLE of a natural parameter for a truncated exponential family of distributions Add to Reading List Source URL: www.ism.ac.jp Language: English - Date: 2016-06-28 03:34:43 Statistics Estimation theory Statistical theory Maximum likelihood estimation Efficient estimator Efficiency Estimator Asymptotic theory Ole Barndorff-Nielsen Likelihood function Two-step M-estimators involving MLE Generalized method of moments
2	Supplement for: A Bayesian model for identifying hierarchically organised states in neural population activity Patrick Putzky1,2,3 , Florian Franzen1,2,3 , Giacomo Bassetto1,3 , Jakob H. Macke1,3 1 Max Planck Institute f Add to Reading List Source URL: www.mackelab.org Language: English - Date: 2016-08-04 15:02:45 Mathematical analysis Statistics Probability Probability distributions Variational Bayesian methods Normal distribution Exponentials Special functions Natural logarithm of 2 Exponential family
3	Journal of Machine Learning Research–2213 Submitted; PublishedNoisy-OR Component Analysis and its Application to Link Analysis Add to Reading List Source URL: people.cs.pitt.edu Language: English - Date: 2006-10-16 22:09:03 Statistics Estimation theory Statistical models Bayesian statistics Statistical natural language processing Statistical theory Expectationmaximization algorithm Variational Bayesian methods Mixture model Exponential family Latent Dirichlet allocation Likelihood function
4	CAUTION: This is an exam from a different semester. The subject matter was comparable, but the text, the audience, the instructor, and the testing environment may have been different from what you will face. Please remem Add to Reading List Source URL: www.math.niu.edu Language: English - Date: 2000-09-29 19:49:49 Logarithms Functions and mappings Mathematical analysis Differential calculus E Natural logarithm Derivative Integral Lambert W function Exponential family
5	PU-BCD: Exponential Family Models for the Coarse- and Fine-Grained All-Words Tasks Jonathan Chang Miroslav Dud´ık, David M. Blei Princeton University Princeton University Add to Reading List Source URL: wordnet.cs.princeton.edu Language: English - Date: 2007-07-08 21:39:23 Computational linguistics Natural language processing Semantics Lexical semantics Word-sense disambiguation WordNet SemEval Model theory
6	Learning with Marginalized Corrupted Features Laurens van der Maaten Delft University of Technology, Mekelweg 4, 2628 CD Delft, THE NETHERLANDS Minmin Chen Add to Reading List Source URL: lvdmaaten.github.io Language: English - Date: 2016-07-16 15:30:43 Statistical classification Probability distributions Exponentials Machine learning Linear classifier Pattern recognition Support vector machine Deep learning Natural exponential family Poisson distribution Normal distribution Loss function
7	Alternatives to the Poisson distribution for modeling mortality projections by Shaul K. Bar-Lev University of Haifa, Israel Add to Reading List Source URL: www.eurandom.tue.nl Language: English - Date: 2009-03-23 10:55:27 Exponentials Actuarial science Regression analysis Data analysis Statistical models Natural exponential family Generalized linear model Probability distribution Variance Statistics Probability and statistics Mathematical analysis
8	Variational Bounds for Mixed-Data Factor Analysis Mohammad Emtiyaz Khan University of British Columbia Vancouver, BC, Canada V6T 1Z4 Add to Reading List Source URL: people.cs.ubc.ca Language: English - Date: 2010-11-01 11:54:31 Bayesian statistics Expectation–maximization algorithm Missing data Statistical natural language processing Mixture model Latent variable model Conjugate prior Maximum likelihood Exponential family Statistics Statistical models Estimation theory
9	Mixed Membership Models David M. Blei Columbia University October 31, 2014 Introduction Add to Reading List Source URL: www.cs.columbia.edu Language: English - Date: 2015-03-12 00:16:19 Latent Dirichlet allocation Mixture model Dirichlet distribution Topic model Exponential family Dirichlet process Variational Bayesian methods Statistics Probability and statistics Statistical natural language processing
10	Deep Exponential Families Rajesh Ranganath Princeton University Linpeng Tang Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2015-02-11 09:55:20 Statistical models Statistical natural language processing Bayesian statistics Exponentials Poisson processes Latent Dirichlet allocation Exponential family Mixture model Gamma distribution Statistics Mathematical analysis Probability and statistics