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» On Wiedemann's Method of Solving Sparse Linear Systems
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JMLR
2006
156views more  JMLR 2006»
13 years 9 months ago
Large Scale Multiple Kernel Learning
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
Sören Sonnenburg, Gunnar Rätsch, Christi...
ICISC
2007
152views Cryptology» more  ICISC 2007»
13 years 10 months ago
Analysis of Multivariate Hash Functions
We analyse the security of new hash functions whose compression function is explicitly defined as a sequence of multivariate equations. First we prove non-universality of certain ...
Jean-Philippe Aumasson, Willi Meier
ICIP
2002
IEEE
14 years 10 months ago
Multigrid image reconstruction from arbitrarily spaced samples
We propose a novel multiresolution-multigrid based signal reconstruction method from arbitrarily spaced samples. The signal is reconstructed on a uniform grid using B-splines basi...
Michael Sühling, Michael Unser, Muthuvel Arig...
SC
1995
ACM
14 years 18 days ago
Parallel Matrix-Vector Product Using Approximate Hierarchical Methods
Matrix-vector products (mat-vecs) form the core of iterative methods used for solving dense linear systems. Often, these systems arise in the solution of integral equations used i...
Ananth Grama, Vipin Kumar, Ahmed H. Sameh
SIAMJO
2008
79views more  SIAMJO 2008»
13 years 9 months ago
A Class of Inexact Variable Metric Proximal Point Algorithms
For the problem of solving maximal monotone inclusions, we present a rather general class of algorithms, which contains hybrid inexact proximal point methods as a special case and ...
Lisandro A. Parente, Pablo A. Lotito, Mikhail V. S...