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» Principal Component Analysis Based on L1-Norm Maximization
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EMMCVPR
2003
Springer
14 years 25 days ago
Asymptotic Characterization of Log-Likelihood Maximization Based Algorithms and Applications
The asymptotic distribution of estimates that are based on a sub-optimal search for the maximum of the log-likelihood function is considered. In particular, estimation schemes that...
Doron Blatt, Alfred O. Hero
TKDE
2008
195views more  TKDE 2008»
13 years 7 months ago
Learning a Maximum Margin Subspace for Image Retrieval
One of the fundamental problems in Content-Based Image Retrieval (CBIR) has been the gap between low-level visual features and high-level semantic concepts. To narrow down this gap...
Xiaofei He, Deng Cai, Jiawei Han
IJON
2007
166views more  IJON 2007»
13 years 7 months ago
Kernel PCA for similarity invariant shape recognition
We present in this paper a novel approach for shape description based on kernel principal component analysis (KPCA). The strength of this method resides in the similarity (rotatio...
Hichem Sahbi
CLEAR
2007
Springer
271views Biometrics» more  CLEAR 2007»
14 years 1 months ago
The AIT Multimodal Person Identification System for CLEAR 2007
This paper presents the person identification system developed at Athens Information Technology and its performance in the CLEAR 2007 evaluations. The system operates on the audiov...
Andreas Stergiou, Aristodemos Pnevmatikakis, Lazar...
SYNASC
2007
IEEE
136views Algorithms» more  SYNASC 2007»
14 years 1 months ago
Wikipedia-Based Kernels for Text Categorization
In recent years several models have been proposed for text categorization. Within this, one of the widely applied models is the vector space model (VSM), where independence betwee...
Zsolt Minier, Zalan Bodo, Lehel Csató