Empirical Likelihood Test for High Dimensional Linear Models Liang Peng1 , Yongcheng Qi2 and Ruodu Wang3 January 7, 2014 Abstract We propose an empirical likelihood method to test whether the coefficients in a possibly h

Source URL: sas.uwaterloo.ca

• Statistics
• Statistical theory
• Estimation theory
• Regression analysis
• Probability distributions
• Parametric statistics
• Bayesian statistics
• Normal distribution
• Linear regression
• Likelihood function

Stat Biosci:206–224 DOIs12561Disease Diagnosis from Immunoassays with Plate to Plate Variability: A Hierarchical Bayesian Approach Oliver A. Entine · Dylan S. Small · Shane T. Jensen ·

Source URL: www-stat.wharton.upenn.edu

• Probability distributions
• Bayesian statistics
• Beta distribution
• Summary statistics
• Mixture model
• Normal distribution
• Prior probability
• Likelihood function
• Mode

Sample Complexity of Composite Likelihood Joseph K. Bradley Carlos Guestrin Carnegie Mellon University

Source URL: select.cs.cmu.edu

• Statistics
• Estimation theory
• Statistical theory
• Maximum likelihood estimation
• Efficient estimator
• Estimator
• Likelihood function
• Normal distribution
• Loss function
• Consistent estimator

Sum of Arbitrarily Dependent Random Variables Ruodu Wang∗ September 15, 2014 Abstract In many classic problems of asymptotic analysis, it appears that the scaled average of a

Source URL: sas.uwaterloo.ca

• Probability distributions
• Central limit theorem
• Stable distribution
• Normal distribution
• Asymptotic distribution
• Expected value
• Relationships among probability distributions
• Cumulative distribution function

DISTRIBUTION OF THE PARTITION FUNCTION MODULO m Ken Ono Annals of Mathematics, 151, 2000, pagesIntroduction and Statement of Results

Source URL: www.mathcs.emory.edu

Learning Policies for Contextual Submodular Prediction Stephane Ross Jiaji Zhou Yisong Yue Debadeepta Dey

Source URL: select.cs.cmu.edu

• Submodular set function
• Automatic summarization
• Statistical classification
• Number theory
• Support vector machine
• Machine learning
• Reinforcement learning
• Mathematical optimization
• Distribution

Riffled Independence for Ranked Data (extended version with proofs) Jonathan Huang, Carlos Guestrin School of Computer Science, Carnegie Mellon University

Source URL: select.cs.cmu.edu

• Fourier analysis
• Probability distributions
• Measure theory
• Fourier transform
• Joseph Fourier
• Permutation
• Random walk
• F-distribution
• Dirac delta function
• Symbol
• Riffle shuffle permutation
• Normal distribution

arXiv:1603.08240v1 [cs.CV] 27 MarDeLight-Net: Decomposing Reflectance Maps into Specular Materials and Natural Illumination Stamatios Georgoulis∗1 , Konstantinos Rematas∗1 , Tobias Ritschel2 , Mario Fritz3 , L

Source URL: arxiv.org

• Shading
• Optics
• Computer graphics
• Radiometry
• Artificial neural networks
• 3D rendering
• Electromagnetic radiation
• Academia
• Reflectance
• Deep lambertian networks
• Phong reflection model
• Bidirectional reflectance distribution function

Some computational aspects of metric fixed point theory Ulrich Kohlenbach Department of Mathematics Darmstadt University of Technology Schlossgartenstraße 7

Source URL: www.mathematik.tu-darmstadt.de

• Mathematical analysis
• Operator theory
• Mathematics
• Computability theory
• Contraction
• Primitive recursive function
• Differential forms on a Riemann surface
• Distribution

Uncovering the riffled independence structure of ranked data

Source URL: select.cs.cmu.edu

• Mathematical analysis
• Probability
• Statistics
• Probability distributions
• Probability theory
• Normal distribution
• Permutation
• F-distribution
• Random walk
• Divisor function
• Conditional independence