Graham Neubig – Non-parametric Bayesian Statistics Non-parametric Bayesian Statistics Graham Neubig

Source URL: www.phontron.com

Automatic Selection of Compiler Options Using Non-parametric Inferential Statistics Masayo Haneda Peter M.W. Knijnenburg Harry A.G. Wijshoff

Source URL: pact05.ce.ucsc.edu

Non-Parametric Jensen-Shannon Divergence Hoang-Vu Nguyen and Jilles Vreeken Max-Planck Institute for Informatics and Saarland University, Germany {hnguyen,jilles}@mpi-inf.mpg.de Abstract. Quantifying the difference betw

Source URL: eda.mmci.uni-saarland.de

• Statistics
• Probability
• Mathematical analysis
• Information theory
• Statistical theory
• Statistical distance
• Probability distributions
• Stable distributions
• KullbackLeibler divergence
• Normal distribution
• Divergence
• Entropy

Supplement Materials to “Non-parametric Regression with Basis Selection from Multiple Libraries” Jeffrey C. Sklar, Junqing Wu, Wendy Meiring, and Yuedong Wang April 29, 2012

Source URL: www.pstat.ucsb.edu

• Statistics
• Estimation theory
• Regression analysis
• Covariance and correlation
• Computational statistics
• Algebra of random variables
• Covariance
• Median
• Normal distribution
• Variance
• Data transformation
• Bootstrapping

Non-parametric estimation of the survivor function for misclassified failure time data Andrew Titman Lancaster University 27 August 2013

Source URL: www.maths.lancs.ac.uk

• Statistics
• Statistical inference
• Estimation theory
• Statistical models
• Signal processing
• Censoring
• Survival analysis
• Nonparametric statistics
• Mixture model
• Bootstrapping
• Likelihood function

B-test: A Non-parametric, Low Variance Kernel Two-sample Test Arthur Gretton Gatsby Unit University College London

Source URL: cs.nyu.edu

• Statistics
• Probability distributions
• Statistical inference
• Computational statistics
• Nonparametric statistics
• Hypothesis testing
• Normal distribution
• Bootstrapping
• Central limit theorem
• Chi-squared distribution
• Median
• Variance

Adjusting for Covariates in Non-Parametric Simultaneous Inference Master’s Thesis - Institute for Mathematical Stochastic Thomas Asendorf

Source URL: www.ams.med.uni-goettingen.de

• Analysis of variance
• Design of experiments
• Statistical tests
• Parametric statistics
• Causal inference
• Analysis of covariance
• Statistical inference
• Experiment
• F-test
• Nonparametric statistics
• Statistical power
• Regression analysis

Non-Parametric Discrete Mixture Model Recovery via Nonnegative Matrix Factorization Stefan Karpinski, John R. Gilbert, Elizabeth M. Belding Department of Computer Science University of California, Santa Barbara {sgk,gilb

Source URL: karpinski.org

• Algebra
• Mathematics
• Matrix theory
• Linear algebra
• Multivariate statistics
• Non-negative matrix factorization
• KullbackLeibler divergence
• Probability distribution
• Singular value decomposition
• Mixture model
• Euclidean algorithm
• Matrix decomposition

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and shar

Source URL: vincent.etter.io

• Recommender system
• Bioinformatics
• Non-parametric statistics
• Regression analysis
• Statistics
• Branch predictor
• Markov chain

On the Simultaneous Analysis of Clinical and Omics Data - a Comparison of Globalboosttest and Pre-validation Techniques Margret-Ruth Oelker and Anne-Laure Boulesteix Abstract In medical research biostatisticians are oft

Source URL: www.ibe.med.uni-muenchen.de

• Non-parametric statistics
• Machine learning
• Estimation theory
• Linear regression
• Resampling
• Cross-validation
• Intelligence quotient
• Statistical power
• Boosting
• Statistics
• Econometrics
• Regression analysis