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ICML
2004
IEEE
14 years 10 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
READING
2004
Springer
14 years 3 months ago
Improving Document Transformation Techniques with Collaborative Learned Term-Based Concepts
Document Transformation techniques have been studied for decades. In this paper, a new approach for a significant improvement is presented based on using a new query expansion met...
Stefan Klink
ECML
2004
Springer
14 years 1 months ago
Population Diversity in Permutation-Based Genetic Algorithm
Abstract. This paper presents an empirical study of population diversity measure and adaptive control of diversity in the context of a permutation-based algorithm for Traveling Sal...
Kenny Qili Zhu, Ziwei Liu
ICML
2004
IEEE
14 years 10 months ago
Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data
In sequence modeling, we often wish to represent complex interaction between labels, such as when performing multiple, cascaded labeling tasks on the same sequence, or when longra...
Charles A. Sutton, Khashayar Rohanimanesh, Andrew ...
ICMLA
2004
13 years 11 months ago
A new discrete binary particle swarm optimization based on learning automata
: The particle swarm is one of the most powerful methods for solving global optimization problems. This method is an adaptive algorithm based on social-psychological metaphor. A po...
Reza Rastegar, Mohammad Reza Meybodi, Kambiz Badie
Machine Learning
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