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» On the Anonymization of Sparse High-Dimensional Data
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CVPR
2005
IEEE
14 years 8 months ago
A Weighted Nearest Mean Classifier for Sparse Subspaces
In this paper we focus on high dimensional data sets for which the number of dimensions is an order of magnitude higher than the number of objects. From a classifier design standp...
Cor J. Veenman, David M. J. Tax
CVPR
2009
IEEE
13 years 10 months ago
Efficiently training a better visual detector with sparse eigenvectors
Face detection plays an important role in many vision applications. Since Viola and Jones [1] proposed the first real-time AdaBoost based object detection system, much effort has ...
Sakrapee Paisitkriangkrai, Chunhua Shen, Jian Zhan...
MICCAI
2010
Springer
13 years 5 months ago
Generalized Sparse Classifiers for Decoding Cognitive States in fMRI
The high dimensionality of functional magnetic resonance imaging (fMRI) data presents major challenges to fMRI pattern classification. Directly applying standard classifiers often ...
Bernard Ng, Arash Vahdat, Ghassan Hamarneh, Rafeef...
ICASSP
2010
IEEE
13 years 7 months ago
Fast signal analysis and decomposition on graphs using the Sparse Matrix Transform
Recently, the Sparse Matrix Transform (SMT) has been proposed as a tool for estimating the eigen-decomposition of high dimensional data vectors [1]. The SMT approach has two major...
Leonardo R. Bachega, Guangzhi Cao, Charles A. Boum...
ICASSP
2011
IEEE
12 years 10 months ago
NAP for high level language identification
Varying channel conditions present a difficult problem for many speech technologies such as language identification (LID). Channel compensation techniques have been shown to sig...
Fred S. Richardson, William M. Campbell