HBase  L2  Cache  Random  Read  Performance   Total  RS  memory:  50GB;  Variable  memory  allocaHons     99%  Response  Latency  (ms)   60  

Source URL: www.n10k.com

Building General Random Effect Models with R and ADMB Jeff Laake, Hans Skaug and Devin Johnson January 23, 2013 The ADMB and Otter Research web sites provide examples of specific random effect models. See http://admb-pro

Source URL: www.admb-project.org

• ADMB
• Cross-platform software
• Free statistical software
• Mixed model
• Logistic regression
• Random variable
• Normal distribution
• Mixed logit
• Exponential random graph models
• Statistics
• Regression analysis
• Probability theory

Appeared in IEEE Conference on Computer Vision and Pattern Recognition (CVPRMulti-View Latent Variable Discriminative Models For Action Recognition Yale Song1 , Louis-Philippe Morency2 , Randall Davis1 1 MIT Com

Source URL: labs.yahoo.com

• Theoretical computer science
• Statistical models
• Bioinformatics
• Hidden Markov model
• Markov chain
• Exponential distribution
• Economic model
• Conditional random field
• Graphical model
• Statistics
• Markov models
• Probability and statistics

26. Derandomization Given a randomized algorithm A, a natural approach towards derandomizing it is to find a method for searching the associated sample space Ω for a good point ω with respect to a given input instanc

Source URL: lovelace.thi.informatik.uni-frankfurt.de

• Random variable
• Method of conditional probabilities
• Event
• Independence
• Expected value
• Randomized algorithm
• Probability space
• Probability theory
• Probability
• Mathematics

Fitting N-mixture models with random observer effects in BUGS and ADMB Richard Chandler, Marc Kéry & Hans Skaug, 20 October[removed]Introduction Abundance is the central state variable in much of ecology and its applica

Source URL: groups.nceas.ucsb.edu

• Mathematical analysis
• Software
• Statistics
• Poisson distribution
• ADMB

Random Features for Large-Scale Kernel Machines Ali Rahimi and Ben Recht Abstract To accelerate the training of kernel machines, we propose to map the input data

Source URL: pages.cs.wisc.edu

• Algebra of random variables
• Operator theory
• Multivariate statistics
• Fourier analysis
• Linear algebra
• Multivariate random variable
• Positive-definite kernel
• Kernel trick
• Gaussian function
• Mathematical analysis
• Mathematics
• Statistics

EN 257: Applied Stochastic Processes Problem Set 1 Douglas Lanman [removed] 2 February 2007

Source URL: mesh.brown.edu

• Ordinary differential equations
• Expected value
• Probability density function
• Dirac delta function
• Random variable
• Quantities of information
• Mutual information
• Mathematical analysis
• Mathematics
• Probability theory

STAT/MATH 394B Winter 2015 Final Exam 1. Richard and nine of his friends are going in two cars to a friend’s cabin. Thomas will be driving one car, and Eileen the other. For reasons of his own, Richard really would

Source URL: www.stat.washington.edu

• Probability distribution
• Random variable
• Inductive reasoning
• Classification rule
• Probability and statistics
• Probability theory
• Measurement

STAT/MATH 395 Problem Session 1. Find the group with the circled number (map on board). Start working together on the circled question. Continue with the next question (1 is the next question after 8). Do as many as you

Source URL: www.stat.washington.edu

• Random variable
• Expected value
• Probability
• Mathematical analysis
• Probability theory
• Randomness
• Probability and statistics

Ch.1 Correlation & Regression 1.1 Mean and Variance [Book, Sect.1.1, 1.2] Let x be a random variable which takes on discrete values. For example, x can be the outcome of a die cast, where the possible values are xi = i,

Source URL: www.ocgy.ubc.ca

• Probability theory
• Summary statistics
• Statistical dependence
• Variance
• Covariance
• Correlation and dependence
• Standard deviation
• Normal distribution
• Sample mean and sample covariance
• Statistics
• Covariance and correlation
• Data analysis