Journal of Machine Learning Research–1816 Submitted 4/05; Revised 10/05; PublishedProbabilistic Non-linear Principal Component Analysis with Gaussian Process Latent Variable Models

Source URL: jmlr.csail.mit.edu

• Principal component analysis
• Expectation–maximization algorithm
• Gaussian process
• Generative topographic map
• Covariance matrix
• Mixture model
• Conjugate prior
• Factor analysis
• Covariance function
• Statistics
• Multivariate statistics
• Kernel principal component analysis

EM for Perceptual Coding and Reinforcement Learning Tasks Yuri Ivanov Bruce Blumberg Alex Pentland

Source URL: characters.media.mit.edu

• Estimation theory
• Expectation–maximization algorithm
• Missing data
• Reinforcement learning
• Mixture model
• Q-learning
• Algorithm
• Pattern recognition
• Statistics
• Machine learning
• Computational statistics

Microsoft Word - OWC CCR 2010.doc

Source URL: www.mauirealestatesearch.com

• Normal distribution
• Expectation–maximization algorithm
• Multivariate normal distribution
• Principal component analysis
• Wishart distribution
• Linear regression
• Symbol
• Conjugate prior
• Statistics
• Estimation theory
• Multivariate statistics

Sparse Bayesian Multi-Task Learning C´edric Archambeau, Shengbo Guo, Onno Zoeter Xerox Research Centre Europe {Cedric.Archambeau, Shengbo.Guo, Onno.Zoeter}@xrce.xerox.com

Source URL: users.cecs.anu.edu.au

• Normal distribution
• Expectation–maximization algorithm
• Multivariate normal distribution
• Principal component analysis
• Wishart distribution
• Linear regression
• Symbol
• Conjugate prior
• Statistics
• Estimation theory
• Multivariate statistics

Expectation Maximization for Weakly Labeled Data Yuri Ivanov MIT Media Laboratory, 20 Ames St., E15-390, Cambridge, MA 02139, USA

Source URL: characters.media.mit.edu

• Maximum likelihood
• Kullback–Leibler divergence
• M-estimator
• Likelihood function
• Reinforcement learning
• Divergence
• Multi-armed bandit
• Marginal likelihood
• Extremum estimator
• Statistics
• Estimation theory
• Expectation–maximization algorithm

COLLEGE EXPECTATIONS The Expectation 1 2

Source URL: www.sec.qld.edu.au

A Meta-Theory of Boundary Detection Benchmarks Xiaodi Hou Computation and Neural Systems, Caltech

Source URL: www.its.caltech.edu

• Expectation–maximization algorithm
• Missing data
• Segmentation
• Statistics
• Image processing
• Estimation theory

4 Drones and privacy 4.1 Remotely piloted aircraft (RPAs) have the potential to pose a serious threat to Australians’ privacy. They can intrude on a person’s or a

Source URL: www.aph.gov.au

• Information privacy
• Internet privacy
• Surveillance
• Hansard
• Expectation of privacy
• Privacy in Australian law
• The right to privacy in New Zealand
• Privacy
• Ethics
• Law

Copyright  2000 by the Genetics Society of America Inference of Population Structure Using Multilocus Genotype Data Jonathan K. Pritchard, Matthew Stephens and Peter Donnelly Department of Statistics, University of O

Source URL: pritchardlab.stanford.edu

• Genetic genealogy
• Classical genetics
• Statistical genetics
• Machine learning
• Hardy–Weinberg principle
• Cluster analysis
• Allele frequency
• Markov chain
• Expectation–maximization algorithm
• Statistics
• Genetics
• Population genetics

Bayesian Estimation of Sparse Smooth Speckle Shape Models for Motion Tracking in Medical Ultrasound MOTIVATION In this work, we aim at adapting the speckle tracking echocardiography (STE) technique for measuring strain i

Source URL: homepages.ulb.ac.be

• Interference
• Cardiac imaging
• Speckle tracking echocardiography
• Speckle pattern
• Expectation–maximization algorithm
• Medical ultrasonography
• Frame
• Medicine
• Medical ultrasound
• Statistics