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JMLR
2011
148views more  JMLR 2011»
13 years 2 months ago
Multitask Sparsity via Maximum Entropy Discrimination
A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
Tony Jebara
IJCNN
2007
IEEE
14 years 1 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
EOR
2007
165views more  EOR 2007»
13 years 7 months ago
Adaptive credit scoring with kernel learning methods
Credit scoring is a method of modelling potential risk of credit applications. Traditionally, logistic regression, linear regression and discriminant analysis are the most popular...
Yingxu Yang
BMCBI
2010
154views more  BMCBI 2010»
13 years 7 months ago
Motif Enrichment Analysis: a unified framework and an evaluation on ChIP data
Background: A major goal of molecular biology is determining the mechanisms that control the transcription of genes. Motif Enrichment Analysis (MEA) seeks to determine which DNA-b...
Robert C. McLeay, Timothy L. Bailey