Sciweavers

ICASSP
2011
IEEE
13 years 4 months ago
Joint blind source separation from second-order statistics: Necessary and sufficient identifiability conditions
This paper considers the problem of joint blind source separation (J-BSS), which appears in many practical problems such as blind deconvolution or functional magnetic resonance im...
Javier Vía, Matthew Anderson, Xi-Lin Li, T&...
TSP
2010
13 years 7 months ago
Selection policy-induced reduction mappings for Boolean networks
Developing computational models paves the way to understanding, predicting, and influencing the long-term behavior of genomic regulatory systems. However, several major challenges ...
Ivan Ivanov, Plamen Simeonov, Noushin Ghaffari, Xi...
JMLR
2010
94views more  JMLR 2010»
13 years 11 months ago
A Rotation Test to Verify Latent Structure
We consider here how to tell whether a latent variable that has been estimated in a multivariate regression context might be real. Often a followup investigation will find a real...
Patrick O. Perry, Art B. Owen
EOR
2006
76views more  EOR 2006»
14 years 13 days ago
Regional development assessment: A structural equation approach
We propose a multivariate statistical framework for regional development assessment based on structural equation modelling with latent variables and show how such methods can be c...
Dario Cziráky, Joze Sambt, Joze Rovan, Jaks...
BMCBI
2006
104views more  BMCBI 2006»
14 years 15 days ago
Semi-supervised discovery of differential genes
Background: Various statistical scores have been proposed for evaluating the significance of genes that may exhibit differential expression between two or more controlled conditio...
Shigeyuki Oba, Shin Ishii
CORR
2008
Springer
85views Education» more  CORR 2008»
14 years 16 days ago
New Estimation Procedures for PLS Path Modelling
: Given R groups of numerical variables X1, ... XR, we assume that each group is the result of one underlying latent variable, and that all latent variables are bound together thro...
Xavier Bry
GRC
2010
IEEE
14 years 1 months ago
Learning Multiple Latent Variables with Self-Organizing Maps
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...
Lili Zhang, Erzsébet Merényi
UAI
2004
14 years 1 months ago
Convolutional Factor Graphs as Probabilistic Models
Based on a recent development in the area of error control coding, we introduce the notion of convolutional factor graphs (CFGs) as a new class of probabilistic graphical models. ...
Yongyi Mao, Frank R. Kschischang, Brendan J. Frey
IFIP12
2004
14 years 1 months ago
Introducing a Star Topology into Latent Class Models for Collaborative Filtering
Latent class models (LCM) represent the high dimensional data in a smaller dimensional space in terms of latent variables. They are able to automatically discover the patterns from...
Gabriela Polcicova, Peter Tiño
UAI
2008
14 years 1 months ago
On Identifying Total Effects in the Presence of Latent Variables and Selection bias
Assume that cause-effect relationships between variables can be described as a directed acyclic graph and the corresponding linear structural equation model We consider the identi...
Manabu Kuroki, Zhihong Cai