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» Semi-Supervised Dimensionality Reduction
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SYRCODIS
2007
126views Database» more  SYRCODIS 2007»
15 years 5 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...
LATINCRYPT
2010
15 years 2 months ago
Accelerating Lattice Reduction with FPGAs
We describe an FPGA accelerator for the Kannan–Fincke– Pohst enumeration algorithm (KFP) solving the Shortest Lattice Vector Problem (SVP). This is the first FPGA implementati...
Jérémie Detrey, Guillaume Hanrot, Xa...
CIKM
2008
Springer
15 years 5 months ago
On low dimensional random projections and similarity search
Random projection (RP) is a common technique for dimensionality reduction under L2 norm for which many significant space embedding results have been demonstrated. However, many si...
Yu-En Lu, Pietro Liò, Steven Hand
154
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NIPS
2004
15 years 5 months ago
Two-Dimensional Linear Discriminant Analysis
Linear Discriminant Analysis (LDA) is a well-known scheme for feature extraction and dimension reduction. It has been used widely in many applications involving high-dimensional d...
Jieping Ye, Ravi Janardan, Qi Li
CVPR
1999
IEEE
16 years 5 months ago
Face Recognition Using Shape and Texture
We introduce in this paper a new face coding and recognition method which employs the Enhanced FLD (Fisher Linear Discrimimant) Model (EFM)on integrated shape (vector) and texture...
Chengjun Liu, Harry Wechsler