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ICONIP
2007
15 years 7 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
JMLR
2006
150views more  JMLR 2006»
15 years 6 months ago
Building Support Vector Machines with Reduced Classifier Complexity
Support vector machines (SVMs), though accurate, are not preferred in applications requiring great classification speed, due to the number of support vectors being large. To overc...
S. Sathiya Keerthi, Olivier Chapelle, Dennis DeCos...
AAECC
2005
Springer
131views Algorithms» more  AAECC 2005»
15 years 6 months ago
Noisy interpolation of sparse polynomials in finite fields
Abstract We consider a polynomial analogue of the hidden number problem introduced by Boneh andVenkatesan, namely the sparse polynomial noisy interpolation problem of recovering an...
Igor Shparlinski, Arne Winterhof
TIT
2002
67views more  TIT 2002»
15 years 6 months ago
Capacity of multiple-transmit multiple-receive antenna architectures
The capacity of wireless communication architectures equipped with multiple transmit and receive antennas and impaired by both noise and cochannel interference is studied. We find ...
Angel Lozano, Antonia Maria Tulino
IPL
2010
134views more  IPL 2010»
15 years 1 months ago
Parameterized algorithm for eternal vertex cover
In this paper we initiate the study of a "dynamic" variant of the classical Vertex Cover problem, the Eternal Vertex Cover problem introduced by Klostermeyer and Mynhard...
Fedor V. Fomin, Serge Gaspers, Petr A. Golovach, D...