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ICCV
2005
IEEE
15 years 3 months ago
A Unifying Approach to Hard and Probabilistic Clustering
We derive the clustering problem from first principles showing that the goal of achieving a probabilistic, or ”hard”, multi class clustering result is equivalent to the algeb...
Ron Zass, Amnon Shashua
ICCS
2005
Springer
15 years 3 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...
CSB
2005
IEEE
115views Bioinformatics» more  CSB 2005»
15 years 3 months ago
A New Clustering Strategy with Stochastic Merging and Removing Based on Kernel Functions
With hierarchical clustering methods, divisions or fusions, once made, are irrevocable. As a result, when two elements in a bottom-up algorithm are assigned to one cluster, they c...
Huimin Geng, Hesham H. Ali
SIGADA
2005
Springer
15 years 3 months ago
Experimental performance analysis of ada programs in cluster system
In this paper, we describe the use of the Ada language for programming in modern cluster systems. The results of experimental performance analysis of Ada and Java programs in a re...
Korochkin Alexandr, Salah Imad, Korochkin Dmitry
CIMCA
2005
IEEE
15 years 3 months ago
A New Evolutionary Algorithm for Determining the Optimal Number of Clusters
Estimating the optimal number of clusters for a dataset is one of the most essential issues in cluster analysis. An improper pre-selection for the number of clusters might easily ...
Wei Lu, Issa Traoré