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» Margin based feature selection - theory and algorithms
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CVPR
2010
IEEE
14 years 3 months ago
Automatic Image Annotation Using Group Sparsity
Automatically assigning relevant text keywords to images is an important problem. Many algorithms have been proposed in the past decade and achieved good performance. Efforts have...
Shaoting Zhang, Junzhou Huang, Yuchi Huang, Yang Y...
AMFG
2007
IEEE
315views Biometrics» more  AMFG 2007»
14 years 2 months ago
Structured Ordinal Features for Appearance-Based Object Representation
In this paper, we propose a novel appearance-based representation, called Structured Ordinal Feature (SOF). SOF is a binary string encoded by combining eight ordinal blocks in a ci...
ShengCai Liao, Zhen Lei, Stan Z. Li, Xiaotong Yuan...
JMLR
2006
124views more  JMLR 2006»
13 years 7 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...
CRV
2006
IEEE
128views Robotics» more  CRV 2006»
13 years 11 months ago
Expert Knowledge Based Automatic Regions-of-Interest (ROI) Selection in Scanned Documents for Digital Image Encryption
Conventional image-oriented cryptographic techniques lack the flexibility needed for content-specific security features such as the concealment of confidential information within ...
Alexander Wong, William Bishop
ML
2002
ACM
167views Machine Learning» more  ML 2002»
13 years 7 months ago
Linear Programming Boosting via Column Generation
We examine linear program (LP) approaches to boosting and demonstrate their efficient solution using LPBoost, a column generation based simplex method. We formulate the problem as...
Ayhan Demiriz, Kristin P. Bennett, John Shawe-Tayl...