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» Theory and Use of the EM Algorithm
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SDM
2004
SIAM
212views Data Mining» more  SDM 2004»
15 years 2 months ago
Clustering with Bregman Divergences
A wide variety of distortion functions, such as squared Euclidean distance, Mahalanobis distance, Itakura-Saito distance and relative entropy, have been used for clustering. In th...
Arindam Banerjee, Srujana Merugu, Inderjit S. Dhil...
MICCAI
2006
Springer
16 years 2 months ago
Segmentation of Brain MRI in Young Children
Abstract. This paper describes an automatic tissue segmentation algorithm for brain MRI of young children. Existing segmentation methods developed for the adult brain do not take i...
Maria Murgasova, Leigh Dyet, A. David Edwards, Mar...
KDD
2002
ACM
118views Data Mining» more  KDD 2002»
16 years 1 months ago
SECRET: a scalable linear regression tree algorithm
Recently there has been an increasing interest in developing regression models for large datasets that are both accurate and easy to interpret. Regressors that have these properti...
Alin Dobra, Johannes Gehrke
ICPR
2000
IEEE
16 years 2 months ago
A Parallel Algorithm for Tracking of Segments in Noisy Edge Images
We present a parallel implementation of a probabilistic algorithm for real time tracking of segments in noisy edge images. Given an initial solution ?a set of segments that reason...
Pedro E. López-de-Teruel, Alberto Ruiz, Jos...
ICDM
2006
IEEE
145views Data Mining» more  ICDM 2006»
15 years 7 months ago
Stability Region Based Expectation Maximization for Model-based Clustering
In spite of the initialization problem, the ExpectationMaximization (EM) algorithm is widely used for estimating the parameters in several data mining related tasks. Most popular ...
Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratn...