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» Semi-Supervised Support Vector Machines
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JMLR
2002
135views more  JMLR 2002»
15 years 3 months ago
Covering Number Bounds of Certain Regularized Linear Function Classes
Recently, sample complexity bounds have been derived for problems involving linear functions such as neural networks and support vector machines. In many of these theoretical stud...
Tong Zhang
116
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SAC
2008
ACM
15 years 3 months ago
Crime scene 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 us...
Ricardo O. Abu Hana, Cinthia Obladen de Almendra F...
149
Voted
ICPR
2010
IEEE
15 years 2 months ago
Human Action Recognition Using Segmented Skeletal Features
We present a novel human action recognition system based on segmented skeletal features which are separated into several human body parts such as face, torso and limbs. Our propos...
Sang Min Yoon, Arjan Kuijper
127
Voted
IEEEHPCS
2010
15 years 2 months ago
An efficient method for face recognition under illumination variations
An efficient method for face recognition which is robust under illumination variations is proposed. The proposed method achieves the illumination invariants based on the reflectan...
A. Nabatchian, E. Abdel-Raheem, M. Ahmadi
146
Voted
PAMI
2010
132views more  PAMI 2010»
15 years 2 months ago
Maximum Likelihood Model Selection for 1-Norm Soft Margin SVMs with Multiple Parameters
—Adapting the hyperparameters of support vector machines (SVMs) is a challenging model selection problem, especially when flexible kernels are to be adapted and data are scarce....
Tobias Glasmachers, Christian Igel