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MCS
2002
Springer
15 years 4 months ago
Boosting and Classification of Electronic Nose Data
Abstract. Boosting methods are known to improve generalization performances of learning algorithms reducing both bias and variance or enlarging the margin of the resulting multi-cl...
Francesco Masulli, Matteo Pardo, Giorgio Sbervegli...
TASLP
2002
156views more  TASLP 2002»
15 years 4 months ago
Musical genre classification of audio signals
Abstract--Musical genres are categorical labels created by humans to characterize pieces of music. A musical genre is characterized by the common characteristics shared by its memb...
George Tzanetakis, Perry R. Cook
ICML
2007
IEEE
16 years 5 months ago
Structural alignment based kernels for protein structure classification
Structural alignments are the most widely used tools for comparing proteins with low sequence similarity. The main contribution of this paper is to derive various kernels on prote...
Sourangshu Bhattacharya, Chiranjib Bhattacharyya, ...
ICML
2004
IEEE
16 years 5 months ago
Decentralized detection and classification using kernel methods
We consider the problem of decentralized detection under constraints on the number of bits that can be transmitted by each sensor. In contrast to most previous work, in which the ...
XuanLong Nguyen, Martin J. Wainwright, Michael I. ...
NIPS
2000
15 years 5 months ago
A Silicon Primitive for Competitive Learning
Competitive learning is a technique for training classification and clustering networks. We have designed and fabricated an 11transistor primitive, that we term an automaximizing ...
David Hsu, Miguel Figueroa, Chris Diorio