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ICONIP
2007
15 years 8 months ago
Principal Component Analysis for Sparse High-Dimensional Data
Abstract. Principal component analysis (PCA) is a widely used technique for data analysis and dimensionality reduction. Eigenvalue decomposition is the standard algorithm for solvi...
Tapani Raiko, Alexander Ilin, Juha Karhunen
ERSA
2010
152views Hardware» more  ERSA 2010»
15 years 4 months ago
Persistent CAD for in-the-field Power Optimization
A major focus within the Integrated Chip (IC) industry is reducing power consumption of devices. In this paper, we explore the idea of persistent CAD algorithms that constantly imp...
Peter Jamieson
ICCV
2009
IEEE
16 years 11 months ago
Non-Negative Matrix Factorization of Partial Track Data for Motion Segmentation
This paper addresses the problem of segmenting lowlevel partial feature point tracks belonging to multiple motions. We show that the local velocity vectors at each instant of th...
Anil M. Cheriyadat and Richard J. Radke
CVPR
2004
IEEE
16 years 8 months ago
Fast Contour Matching Using Approximate Earth Mover's Distance
Weighted graph matching is a good way to align a pair of shapes represented by a set of descriptive local features; the set of correspondences produced by the minimum cost matchin...
Kristen Grauman, Trevor Darrell
ICCV
2001
IEEE
16 years 8 months ago
Image Segmentation with Minimum Mean Cut
We introduce a new graph-theoretic approach to image segmentation based on minimizing a novel class of `mean cut' cost functions. Minimizing these cost functions corresponds ...
Song Wang, Jeffrey Mark Siskind