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PAMI
2008
200views more  PAMI 2008»
13 years 7 months ago
Principal Component Analysis Based on L1-Norm Maximization
In data-analysis problems with a large number of dimension, principal component analysis based on L2-norm (L2PCA) is one of the most popular methods, but L2-PCA is sensitive to out...
Nojun Kwak
IPPS
2003
IEEE
14 years 29 days ago
Channel Assignment on Strongly-Simplicial Graphs
Given a vector ( 1 2 ::: t) of non increasing positive integers, and an undirected graph G = (V E), an L( 1 2 ::: t)-coloring of G is a function f from the vertex set V to a set o...
Alan A. Bertossi, Maria Cristina Pinotti, Romeo Ri...
NIPS
1998
13 years 9 months ago
Using Analytic QP and Sparseness to Speed Training of Support Vector Machines
Training a Support Vector Machine (SVM) requires the solution of a very large quadratic programming (QP) problem. This paper proposes an algorithm for training SVMs: Sequential Mi...
John C. Platt
ISPD
2000
ACM
139views Hardware» more  ISPD 2000»
14 years 1 days ago
Critical area computation for missing material defects in VLSI circuits
We address the problem of computing critical area for missing material defects in a circuit layout. The extraction of critical area is the main computational problem in VLSI yield...
Evanthia Papadopoulou
CVPR
2011
IEEE
13 years 5 months ago
Sparsity-based Image Denoising via Dictionary Learning and Structural Clustering
Where does the sparsity in image signals come from? Local and nonlocal image models have supplied complementary views toward the regularity in natural images the former attempts t...
Weisheng Dong, Xin Li