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SIAMMAX
2010
105views more  SIAMMAX 2010»
12 years 11 months ago
Construction of Covariance Matrices with a Specified Discrepancy Function Minimizer, with Application to Factor Analysis
The main goal of this paper is to develop a numerical procedure for construction of covariance matrices such that for a given covariance structural model and a discrepancy function...
So Yeon Chun, A. Shapiro
TSP
2011
90views more  TSP 2011»
12 years 11 months ago
Radar HRRP Statistical Recognition With Local Factor Analysis by Automatic Bayesian Ying-Yang Harmony Learning
—Radar high-resolution range profiles (HRRPs) are typical high-dimensional, non-Gaussian and interdimension dependently distributed data, the statistical modelling of which is a...
Lei Shi, Penghui Wang, Hongwei Liu, Lei Xu, Zheng ...
BMCBI
2010
216views more  BMCBI 2010»
12 years 11 months ago
Bayesian Inference of the Number of Factors in Gene-Expression Analysis: Application to Human Virus Challenge Studies
Background: Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors f...
Bo Chen, Minhua Chen, John William Paisley, Aimee ...
ICWSM
2009
13 years 2 months ago
An Examination of Language Use in Online Dating Profiles
This paper contributes to the study of self-presentation in online dating systems by performing a factor analysis on the text portions of online profiles. Findings include a simil...
Meenakshi Nagarajan, Marti A. Hearst
CORR
2010
Springer
139views Education» more  CORR 2010»
13 years 4 months ago
The semantic mapping of words and co-words in contexts
Meaning can be generated when information is related at a systemic level. Such a system can be an observer, but also a discourse, for example, operationalized as a set of document...
Loet Leydesdorff, Kasper Welbers
ICASSP
2010
IEEE
13 years 4 months ago
On the use of speaker superfactors for speaker recognition
We propose a new method to characterize a speaker within the Joint Factor Analysis (JFA) framework. Scoring within the JFA framework can be costly and a new method was proposed to...
Nicolas Scheffer, Robbie Vogt
NIPS
2004
13 years 5 months ago
Unsupervised Variational Bayesian Learning of Nonlinear Models
In this paper we present a framework for using multi-layer perceptron (MLP) networks in nonlinear generative models trained by variational Bayesian learning. The nonlinearity is h...
Antti Honkela, Harri Valpola
DATESO
2004
116views Database» more  DATESO 2004»
13 years 5 months ago
Using Blind Search and Formal Concepts for Binary Factor Analysis
Binary Factor Analysis (BFA, also known as Boolean Factor Analysis) may help with understanding collections of binary data. Since we can take collections of text documents as binar...
Ales Keprt
CLA
2004
13 years 5 months ago
Binary Factor Analysis with Help of Formal Concepts
Binary factor analysis (BFA, also known as Boolean Factor Analysis) is a nonhierarchical analysis of binary data, based on reduction of binary space dimension. It allows us to find...
Ales Keprt, Václav Snásel
AUSAI
2007
Springer
13 years 8 months ago
Branching Rules for Satisfiability Analysed with Factor Analysis
Factor analysis is a statistical technique for reducing the number of factors responsible for a matrix of correlations to a smaller number of factors that may reflect underlying va...
Richard J. Wallace, Stuart Bain