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ICASSP
2010
IEEE
15 years 7 months ago
Hierarchical Gaussian Mixture Model
Gaussian mixture models (GMMs) are a convenient and essential tool for the estimation of probability density functions. Although GMMs are used in many research domains from image ...
Vincent Garcia, Frank Nielsen, Richard Nock
166
Voted
AUTOMATICA
2006
109views more  AUTOMATICA 2006»
15 years 6 months ago
Closed-loop subspace identification using the parity space
It is known that many subspace algorithms give biased estimates for closed-loop data due to the existence of feedback. In this paper we present a new subspace identification metho...
Jin Wang, S. Joe Qin
CSDA
2006
83views more  CSDA 2006»
15 years 6 months ago
Linear grouping using orthogonal regression
A new method to detect different linear structures in a data set, called Linear Grouping Algorithm (LGA), is proposed. LGA is useful for investigating potential linear patterns in...
Stefan Van Aelst, Xiaogang Wang, Ruben H. Zamar, R...
IPM
2006
130views more  IPM 2006»
15 years 6 months ago
Exploiting structural information for semi-structured document categorization
This paper examines several different approaches to exploiting structural information in semi-structured document categorization. The methods under consideration are designed for ...
Andrej Bratko, Bogdan Filipic
124
Voted
CSDA
2007
81views more  CSDA 2007»
15 years 6 months ago
A stochastic EM algorithm for a semiparametric mixture model
Recently, there has been a considerable interest in finite mixture models with semi-/non-parametric component distributions. Identifiability of such model parameters is generall...
Laurent Bordes, Didier Chauveau, Pierre Vandekerkh...