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» Regular Texture Analysis as Statistical Model Selection
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KDD
2010
ACM
274views Data Mining» more  KDD 2010»
13 years 11 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
ICANNGA
2009
Springer
134views Algorithms» more  ICANNGA 2009»
14 years 2 months ago
A Generative Model for Self/Non-self Discrimination in Strings
A statistical generative model is presented as an alternative to negative selection in anomaly detection of string data. We extend the probabilistic approach to binary classificat...
Matti Pöllä
BMCBI
2011
12 years 11 months ago
Dissecting protein loops with a statistical scalpel suggests a functional implication of some structural motifs
Background: One of the strategies for protein function annotation is to search particular structural motifs that are known to be shared by proteins with a given function. Results:...
Leslie Regad, Juliette Martin, Anne-Claude Camprou...
WSDM
2012
ACM
301views Data Mining» more  WSDM 2012»
12 years 3 months ago
Learning evolving and emerging topics in social media: a dynamic nmf approach with temporal regularization
As massive repositories of real-time human commentary, social media platforms have arguably evolved far beyond passive facilitation of online social interactions. Rapid analysis o...
Ankan Saha, Vikas Sindhwani
BMEI
2009
IEEE
13 years 8 months ago
A Kurtosis and Skewness Based Criterion for Model Selection on Gaussian Mixture
The Gaussian mixture model is a powerful statistical tool in data modeling and analysis. Generally, the EM algorithm is utilized to learn the parameters of the Gaussian mixture. Ho...
Lin Wang, Jinwen Ma