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ICDAR
2003
IEEE
14 years 1 months ago
Unsupervised Feature Selection Using Multi-Objective Genetic Algorithms for Handwritten Word Recognition
In this paper a methodology for feature selection in unsupervised learning is proposed. It makes use of a multiobjective genetic algorithm where the minimization of the number of ...
Marisa E. Morita, Robert Sabourin, Flávio B...
ICPR
2008
IEEE
14 years 2 months ago
Online anomal movement detection based on unsupervised incremental learning
We propose an online anomal movement detection method using incremental unsupervised learning. As the feature for discrimination, we extract the principal component of the spatio-...
Kyoko Sudo, Tatsuya Osawa, Hidenori Tanaka, Hideki...
AAAI
2000
13 years 9 months ago
Unsupervised Learning and Interactive Jazz/Blues Improvisation
We present a new domain for unsupervised learning: automatically customizing the computer to a specific melodic performer by merely listening to them improvise. We also describe B...
Belinda Thom
ACL
2004
13 years 9 months ago
Annealing Techniques For Unsupervised Statistical Language Learning
Exploiting unannotated natural language data is hard largely because unsupervised parameter estimation is hard. We describe deterministic annealing (Rose et al., 1990) as an appea...
Noah A. Smith, Jason Eisner
FLAIRS
2004
13 years 9 months ago
Clustering Spatial Data in the Presence of Obstacles
Clustering is a form of unsupervised machine learning. In this paper, we proposed the DBRS_O method to identify clusters in the presence of intersected obstacles. Without doing an...
Xin Wang, Howard J. Hamilton