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IJCNN
2006
IEEE
14 years 1 months ago
Learning the Kernel in Mahalanobis One-Class Support Vector Machines
— In this paper, we show that one-class SVMs can also utilize data covariance in a robust manner to improve performance. Furthermore, by constraining the desired kernel function ...
Ivor W. Tsang, James T. Kwok, Shutao Li
BMCBI
2008
170views more  BMCBI 2008»
13 years 7 months ago
A genetic approach for building different alphabets for peptide and protein classification
Background: In this paper, it is proposed an optimization approach for producing reduced alphabets for peptide classification, using a Genetic Algorithm. The classification task i...
Loris Nanni, Alessandra Lumini
AAAI
2010
13 years 9 months ago
Smooth Optimization for Effective Multiple Kernel Learning
Multiple Kernel Learning (MKL) can be formulated as a convex-concave minmax optimization problem, whose saddle point corresponds to the optimal solution to MKL. Most MKL methods e...
Zenglin Xu, Rong Jin, Shenghuo Zhu, Michael R. Lyu...
BMCBI
2006
180views more  BMCBI 2006»
13 years 7 months ago
Building multiclass classifiers for remote homology detection and fold recognition
Motivation Protein remote homology prediction and fold recognition are central problems in computational biology. Supervised learning algorithms based on support vector machines a...
Huzefa Rangwala, George Karypis
ICML
2007
IEEE
14 years 8 months ago
An integrated approach to feature invention and model construction for drug activity prediction
We present a new machine learning approach for 3D-QSAR, the task of predicting binding affinities of molecules to target proteins based on 3D structure. Our approach predicts bind...
David Page, Jesse Davis, Soumya Ray, Vítor ...