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ICML
2004
IEEE
16 years 7 months ago
K-means clustering via principal component analysis
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
Chris H. Q. Ding, Xiaofeng He
NPL
1998
135views more  NPL 1998»
15 years 6 months ago
Local Adaptive Subspace Regression
Abstract. Incremental learning of sensorimotor transformations in high dimensional spaces is one of the basic prerequisites for the success of autonomous robot devices as well as b...
Sethu Vijayakumar, Stefan Schaal
GECCO
2007
Springer
176views Optimization» more  GECCO 2007»
16 years 28 days ago
The effect of learning on life history evolution
A series of evolutionary neural network simulations are presented which explore the hypothesis that learning factors can result in the evolution of long periods of parental protec...
John A. Bullinaria
GECCO
2009
Springer
109views Optimization» more  GECCO 2009»
15 years 11 months ago
A genetic algorithm for learning significant phrase patterns in radiology reports
Radiologists disagree with each other over the characteristics and features of what constitutes a normal mammogram and the terminology to use in the associated radiology report. R...
Robert M. Patton, Thomas E. Potok, Barbara G. Beck...
ACMICEC
2006
ACM
110views ECommerce» more  ACMICEC 2006»
15 years 10 months ago
Learning inventory management strategies for commodity supply chains with customer satisfaction
In this paper, we look at a supply chain of commodity goods where customer demand is uncertain and partly based on reputation, and where raw material replenishment is uncertain in...
Jeroen van Luin, Han La Poutré, J. Will M. ...