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Hyperparameter
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#	Item
21	Stock assessment of short-lived invertebrates using hierarchical Bayesian models Add to Reading List Source URL: www.mssanz.org.au Language: English - Date: 2013-01-16 21:22:25 Stock assessment Hierarchical Bayes model Prior probability Bayesian inference Hyperparameter Maximum sustainable yield Bycatch Hyperprior Statistics Bayesian statistics Deviance information criterion
22	PDF Document Add to Reading List Source URL: research.microsoft.com Language: English - Date: 2013-05-15 06:48:19 Probability distribution Bayesian statistics Statistics Hyperparameter
23	PDF Document Add to Reading List Source URL: www.spatial-statistics.com Language: English - Date: 2000-10-13 17:24:39 Statistical theory Statistical inference Regression analysis Spatial analysis Bayesian inference Hyperparameter Linear regression Nuisance parameter Prior probability Statistics Bayesian statistics Estimation theory
24	UNIVERSITY OF SOUTHAMPTON Interpretable Modelling with Sparse Kernels Add to Reading List Source URL: users.ecs.soton.ac.uk Language: English - Date: 2002-08-20 18:16:49 Markov chain Monte Carlo Bayesian inference Variational Bayesian methods Hyperparameter Machine learning Gibbs sampling Statistics Bayesian statistics Bayesian network
25	Hierarchical Regression David M. Blei Columbia University December 3, 2014 Hierarchical models are a cornerstone of data analysis, especially with large grouped data. Another way to look at “big data” is that we have Add to Reading List Source URL: www.cs.columbia.edu Language: English - Date: 2015-03-12 00:16:19 Bayesian statistics Econometrics Actuarial science Hyperparameter Linear regression Mixture model Generalized linear model Multilevel model Logistic regression Statistics Regression analysis Statistical models
26	NeuroImage–206 Contents lists available at SciVerse ScienceDirect NeuroImage journal homepage: www.elsevier.com/locate/ynimg Add to Reading List Source URL: psiexp.ss.uci.edu Language: English - Date: 2013-08-28 14:00:44 Cognitive science Science Neural networks ACT-R Cognitive architecture Functional magnetic resonance imaging Hyperparameter Artificial neural network Computational neuroscience Statistics Neuroscience
27	HYPERPARAMETERS: OPTIMIZE, OR INTEGRATE OUT? David J.C. MacKay Cavendish Laboratory, Cambridge, CB3 0HE. United Kingdom. Add to Reading List Source URL: bayes.wustl.edu Language: English - Date: 2010-12-21 17:21:30 Estimation theory Statistical inference Normal distribution Mixture model Hyperparameter Maximum likelihood Variational Bayesian methods Least squares support vector machine Statistics Bayesian statistics Statistical theory
28	Multi-Task Bayesian Optimization Kevin Swersky Department of Computer Science University of Toronto Add to Reading List Source URL: papers.nips.cc Language: English - Date: 2014-11-25 16:20:14 Machine learning Estimation theory Mathematical optimization Operations research Hyperparameter Global optimization Cross-validation Bayesian inference Likelihood function Statistics Bayesian statistics Statistical theory
29	UAI[removed]ASUNCION ET AL. 27 Add to Reading List Source URL: arxiv.org Language: English - Date: 2012-05-13 20:03:54 Variational Bayesian methods Latent Dirichlet allocation Expectation–maximization algorithm Dirichlet distribution Bayesian inference Probabilistic latent semantic analysis Hyperparameter Statistics Bayesian statistics Statistical natural language processing
30	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: users.cecs.anu.edu.au Language: English - Date: 2009-06-21 14:46:52 Theoretical computer science Semi-supervised learning Supervised learning Graph Tree Flow network Active learning Graph theory Machine learning Mathematics