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» Learning of Boolean Functions Using Support Vector Machines
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ICPR
2000
IEEE
14 years 10 months ago
General Bias/Variance Decomposition with Target Independent Variance of Error Functions Derived from the Exponential Family of D
An important theoretical tool in machine learning is the bias/variance decomposition of the generalization error. It was introduced for the mean square error in [3]. The bias/vari...
Jakob Vogdrup Hansen, Tom Heskes
ICML
2004
IEEE
14 years 10 months ago
Nonparametric classification with polynomial MPMC cascades
A new class of nonparametric algorithms for high-dimensional binary classification is proposed using cascades of low dimensional polynomial structures. Construction of polynomial ...
Sander M. Bohte, Markus Breitenbach, Gregory Z. Gr...
ICRA
2008
IEEE
229views Robotics» more  ICRA 2008»
14 years 3 months ago
Learning of moving cast shadows for dynamic environments
Abstract— We propose a novel online framework for detecting moving shadows in video sequences using statistical learning techniques. In this framework, Support Vector Machines ar...
Ajay J. Joshi, Nikolaos Papanikolopoulos
WCE
2007
13 years 10 months ago
A Comparison of Classification Techniques for Technical Text Passages
— Our work explores the use of several text categorization techniques for classification of manufacturing quality defect and service shop data sets into fixed categories. Althoug...
Mark M. Kornfein, Helena Goldfarb
BMCBI
2010
113views more  BMCBI 2010»
13 years 9 months ago
Prediction of FAD interacting residues in a protein from its primary sequence using evolutionary information
Background: Flavin binding proteins (FBP) plays a critical role in several biological functions such as electron transport system (ETS). These flavoproteins contain very tightly b...
Nitish K. Mishra, Gajendra P. S. Raghava