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NIPS
2003
15 years 7 months ago
An Iterative Improvement Procedure for Hierarchical Clustering
We describe a procedure which finds a hierarchical clustering by hillclimbing. The cost function we use is a hierarchical extension of the  -means cost; our local moves are tree...
David Kauchak, Sanjoy Dasgupta
AUTOMATICA
2005
50views more  AUTOMATICA 2005»
15 years 6 months ago
Identification of piecewise affine systems based on statistical clustering technique
This paper is concerned with the identification of a class of piecewise affine systems called a piecewise affine autoregressive exogenous (PWARX) model. The PWARX model is compose...
Hayato Nakada, Kiyotsugu Takaba, Tohru Katayama
BC
2005
77views more  BC 2005»
15 years 6 months ago
Motion repulsion arises from stimulus statistics when analyzed with a clustering algorithm
Motion repulsion is the perceived enlargement of the angle between the directions of motion of two transparently moving patterns. An explanation of this illusion has long been soug...
Alireza S. Mahani, Anders E. Carlsson, Ralf Wessel
ISIM
2007
15 years 7 months ago
Performance Comparison of Distributed Object Server Implementation
Abstract. In this paper we presentperformancemeasurementsin a cluster environment. First, we briefly explain our version of optimistic concurrency control and load balance.Then we ...
Petr Kroha, Mathias Kurth, Michael Fleischer
ESANN
2006
15 years 7 months ago
Hierarchical analysis of GSM network performance data
In this study, a method for hierarchical examination and visualization of GSM data using the Self-Organizing Map (SOM) is described. The data is examined in few phases. At first te...
Mikko Multanen, Kimmo Raivio, Pasi Lehtimäki