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» A Method for Dynamic Clustering of Data
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NECO
2002
104views more  NECO 2002»
14 years 11 months ago
An Unsupervised Ensemble Learning Method for Nonlinear Dynamic State-Space Models
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
Harri Valpola, Juha Karhunen
ICCS
2005
Springer
15 years 5 months ago
Clustering Using Adaptive Self-organizing Maps (ASOM) and Applications
Abstract. This paper presents an innovative, adaptive variant of Kohonen’s selforganizing maps called ASOM, which is an unsupervised clustering method that adaptively decides on ...
Yong Wang, Chengyong Yang, Kalai Mathee, Giri Nara...
ICDM
2005
IEEE
136views Data Mining» more  ICDM 2005»
15 years 5 months ago
Pairwise Symmetry Decomposition Method for Generalized Covariance Analysis
We propose a new theoretical framework for generalizing the traditional notion of covariance. First, we discuss the role of pairwise cross-cumulants by introducing a cluster expan...
Tsuyoshi Idé
ACL
1993
15 years 1 months ago
Distributional Clustering of English Words
We describe and evaluate experimentally a method for clustering words according to their distribution in particular syntactic contexts. Words are represented by the relative frequ...
Fernando C. N. Pereira, Naftali Tishby, Lillian Le...
SISAP
2009
IEEE
134views Data Mining» more  SISAP 2009»
15 years 6 months ago
EGNAT: A Fully Dynamic Metric Access Method for Secondary Memory
—We introduce a novel metric space search data structure called EGNAT, which is fully dynamic and designed for secondary memory. The EGNAT is based on Brin’s GNAT static index,...
Roberto Uribe Paredes, Gonzalo Navarro