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ICPR
2008
IEEE
14 years 8 months ago
Multiple kernel learning from sets of partially matching image features
Abstract: Kernel classifiers based on Support Vector Machines (SVM) have achieved state-ofthe-art results in several visual classification tasks, however, recent publications and d...
Guo ShengYang, Min Tan, Si-Yao Fu, Zeng-Guang Hou,...
CRV
2009
IEEE
115views Robotics» more  CRV 2009»
14 years 2 months ago
Learning Model Complexity in an Online Environment
In this paper we introduce the concept and method for adaptively tuning the model complexity in an online manner as more examples become available. Challenging classification pro...
Dan Levi, Shimon Ullman
AC
2003
Springer
13 years 11 months ago
Influence of Location over Several Classifiers in 2D and 3D Face Verification
In this paper two methods for human face recognition and the influence of location mistakes are shown. First one, Principal Components Analysis (PCA), has been one of the most appl...
Susana Mata, Cristina Conde, Araceli Sánche...
NIPS
2003
13 years 8 months ago
Max-Margin Markov Networks
In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the ...
Benjamin Taskar, Carlos Guestrin, Daphne Koller
BMCBI
2007
130views more  BMCBI 2007»
13 years 7 months ago
Exploiting residue-level and profile-level interface propensities for usage in binding sites prediction of proteins
Background: Recognition of binding sites in proteins is a direct computational approach to the characterization of proteins in terms of biological and biochemical function. Residu...
Qiwen Dong, Xiaolong Wang, Lei Lin, Yi Guan