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AAAI
2010
13 years 4 months ago
Multilinear Maximum Distance Embedding Via L1-Norm Optimization
Dimensionality reduction plays an important role in many machine learning and pattern recognition tasks. In this paper, we present a novel dimensionality reduction algorithm calle...
Yang Liu, Yan Liu, Keith C. C. Chan
ICPR
2008
IEEE
14 years 2 months ago
Joint segmentation and registration of elastically deformable objects
We present a new approach to the general problem of template-based segmentation, detection, and registration. This joint problem is highly nonlinear and high dimensional, due to t...
Gilad Cohen, Joseph M. Francos, Rami Hagege
WSCG
2001
106views more  WSCG 2001»
13 years 9 months ago
An Alternative Approach for Pattern Detection Applied to Materials Characterization
The problem of detecting specific patterns in images of materials obtained through High Resolution Transmission Electron Microscopy is addressed. A supervised classification metho...
Raul Queiroz Feitosa, Guilherme Lúcio Abelh...
SYRCODIS
2007
126views Database» more  SYRCODIS 2007»
13 years 8 months ago
Concept Lattice Reduction by Singular Value Decomposition
High complexity of lattice construction algorithms and uneasy way of visualising lattices are two important problems connected with the formal concept analysis. Algorithm complexi...
Václav Snásel, Martin Polovincak, Hu...
KDD
2005
ACM
118views Data Mining» more  KDD 2005»
14 years 8 months ago
On the use of linear programming for unsupervised text classification
We propose a new algorithm for dimensionality reduction and unsupervised text classification. We use mixture models as underlying process of generating corpus and utilize a novel,...
Mark Sandler