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SSPR
2010
Springer
14 years 10 months ago
Non-parametric Mixture Models for Clustering
Mixture models have been widely used for data clustering. However, commonly used mixture models are generally of a parametric form (e.g., mixture of Gaussian distributions or GMM),...
Pavan Kumar Mallapragada, Rong Jin, Anil K. Jain
ECAI
2008
Springer
15 years 1 months ago
An Ensemble of Classifiers for coping with Recurring Contexts in Data Streams
Abstract. This paper proposes a general framework for classifying data streams by exploiting incremental clustering in order to dynamically build and update an ensemble of incremen...
Ioannis Katakis, Grigorios Tsoumakas, Ioannis P. V...
PKDD
2005
Springer
122views Data Mining» more  PKDD 2005»
15 years 5 months ago
A Probabilistic Clustering-Projection Model for Discrete Data
For discrete co-occurrence data like documents and words, calculating optimal projections and clustering are two different but related tasks. The goal of projection is to find a ...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...
PAKDD
2004
ACM
97views Data Mining» more  PAKDD 2004»
15 years 5 months ago
Further Applications of a Particle Visualization Framework
Our previous work introduced a 3D particle visualization framework that viewed each data point as being a particle affected by gravitational forces. We showed the use of this tool ...
Ke Yin, Ian Davidson
PAMI
2008
119views more  PAMI 2008»
14 years 11 months ago
Triplet Markov Fields for the Classification of Complex Structure Data
We address the issue of classifying complex data. We focus on three main sources of complexity, namely, the high dimensionality of the observed data, the dependencies between these...
Juliette Blanchet, Florence Forbes