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» Learning of Boolean Functions Using Support Vector Machines
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APBC
2004
138views Bioinformatics» more  APBC 2004»
13 years 10 months ago
Whole-Genome Functional Classification of Genes by Latent Semantic Analysis on Microarray Data
Quantitative simultaneous monitoring of the expression levels of thousands of genes under various experimental conditions is now possible using microarray experiments. The resulti...
See-Kiong Ng, Zexuan Zhu, Yew-Soon Ong
SMC
2010
IEEE
132views Control Systems» more  SMC 2010»
13 years 7 months ago
Selection of SIFT feature points for scene description in robot vision
This paper presents a method for selection of SIFT(Scale-Invariant Feature Transform) feature points using OC-SVM (One Class-Support Vector Machines). We proposed the method for au...
Yuya Utsumi, Masahiro Tsukada, Hirokazu Madokoro, ...
ECML
2005
Springer
14 years 2 months ago
Using Advice to Transfer Knowledge Acquired in One Reinforcement Learning Task to Another
We present a method for transferring knowledge learned in one task to a related task. Our problem solvers employ reinforcement learning to acquire a model for one task. We then tra...
Lisa Torrey, Trevor Walker, Jude W. Shavlik, Richa...
MHCI
2009
Springer
14 years 3 months ago
Automatic mobile menu customization based on user operation history
Mobile devices are becoming more and more difficult to use due to the sheer number of functions now supported. In this paper, we propose a menu customization system that ranks fun...
Yusuke Fukazawa, Mirai Hara, Masashi Onogi, Hideto...
ISCI
2007
130views more  ISCI 2007»
13 years 9 months ago
Learning to classify e-mail
In this paper we study supervised and semi-supervised classification of e-mails. We consider two tasks: filing e-mails into folders and spam e-mail filtering. Firstly, in a sup...
Irena Koprinska, Josiah Poon, James Clark, Jason C...