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» Support Vector Machines for Multi-class Classification
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JMLR
2006
124views more  JMLR 2006»
14 years 11 months ago
A Direct Method for Building Sparse Kernel Learning Algorithms
Many kernel learning algorithms, including support vector machines, result in a kernel machine, such as a kernel classifier, whose key component is a weight vector in a feature sp...
Mingrui Wu, Bernhard Schölkopf, Gökhan H...
BMCBI
2008
114views more  BMCBI 2008»
14 years 12 months ago
Combining classifiers for improved classification of proteins from sequence or structure
Background: Predicting a protein's structural or functional class from its amino acid sequence or structure is a fundamental problem in computational biology. Recently, there...
Iain Melvin, Jason Weston, Christina S. Leslie, Wi...
JUCS
2008
136views more  JUCS 2008»
14 years 11 months ago
Crime Scene Representation (2D, 3D, Stereoscopic Projection) and Classification
: In this paper we provide a study about crime scenes and its features used in criminal investigations. We argue that the crime scene provides a large set of features that can be u...
Ricardo O. Abu Hana, Cinthia Obladen de Almendra F...
EMNLP
2009
14 years 9 months ago
Reverse Engineering of Tree Kernel Feature Spaces
We present a framework to extract the most important features (tree fragments) from a Tree Kernel (TK) space according to their importance in the target kernelbased machine, e.g. ...
Daniele Pighin, Alessandro Moschitti
ECML
2006
Springer
15 years 3 months ago
Multiple-Instance Learning Via Random Walk
This paper presents a decoupled two stage solution to the multiple-instance learning (MIL) problem. With a constructed affinity matrix to reflect the instance relations, a modified...
Dong Wang, Jianmin Li, Bo Zhang