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» A Kernel Method for the Two-Sample Problem
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ML
2002
ACM
220views Machine Learning» more  ML 2002»
15 years 2 months ago
Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
Peter Sollich
CSE
2009
IEEE
15 years 6 months ago
A Comparative Study of Blocking Storage Methods for Sparse Matrices on Multicore Architectures
Sparse Matrix-Vector multiplication (SpMV) is a very challenging computational kernel, since its performance depends greatly on both the input matrix and the underlying architectur...
Vasileios Karakasis, Georgios I. Goumas, Nectarios...
AAAI
2007
15 years 4 months ago
Biomind ArrayGenius and GeneGenius: Web Services Offering Microarray and SNP Data Analysis via Novel Machine Learning Methods
Analysis of postgenomic biological data (such as microarray and SNP data) is a subtle art and science, and the statistical methods most commonly utilized sometimes prove inadequat...
Ben Goertzel, Cassio Pennachin, Lúcio de So...
149
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ICIP
2008
IEEE
16 years 4 months ago
Subspace-based methods for image registration and super-resolution
Super-resolution algorithms combine multiple low resolution images into a single high resolution image. They have received a lot of attention recently in various application domai...
Patrick Vandewalle, Loïc Baboulaz, Pier Luigi...
TSP
2010
14 years 9 months ago
Sampling piecewise sinusoidal signals with finite rate of innovation methods
We consider the problem of sampling piecewise sinusoidal signals. Classical sampling theory does not enable perfect reconstruction of such signals since they are not bandlimited. ...
Jesse Berent, Pier Luigi Dragotti, Thierry Blu