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ALT
2000
Springer
14 years 4 months ago
On the Noise Model of Support Vector Machines Regression
Abstract. Support Vector Machines Regression (SVMR) is a learning technique where the goodness of fit is measured not by the usual quadratic loss function (the mean square error),...
Massimiliano Pontil, Sayan Mukherjee, Federico Gir...
DASFAA
2009
IEEE
133views Database» more  DASFAA 2009»
14 years 2 months ago
Probabilistic Ranking in Uncertain Vector Spaces
Abstract. In many application domains, e.g. sensor databases, traffic management or recognition systems, objects have to be compared based on positionally and existentially uncert...
Thomas Bernecker, Hans-Peter Kriegel, Matthias Ren...
ISMIR
2005
Springer
145views Music» more  ISMIR 2005»
14 years 1 months ago
An Investigation of Feature Models for Music Genre Classification Using the Support Vector Classifier
In music genre classification the decision time is typically of the order of several seconds, however, most automatic music genre classification systems focus on short time feat...
Anders Meng, John Shawe-Taylor
ICPR
2010
IEEE
13 years 10 months ago
Compressing Sparse Feature Vectors Using Random Ortho-Projections
In this paper we investigate the usage of random ortho-projections in the compression of sparse feature vectors. The study is carried out by evaluating the compressed features in ...
Esa Rahtu, Mikko Salo, Janne Heikkilä
BIOCOMP
2006
13 years 9 months ago
Support Vector Machines for Predicting microRNA Hairpins
- microRNAs (miRNAs) are 20-22 nt noncoding RNAs which are rapidly emerging as crucial regulators of gene expression in plants and animals. Identification of the hairpins which yie...
Karol Szafranski, Molly Megraw, Martin Reczko, Art...