54 search results - page 6 / 11 » Hardness of Approximating the Closest Vector Problem with Pr... |
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
CDC
2009
IEEE
13 years 10 months ago
2009
IEEE
—In kernel based regression techniques (such as Support Vector Machines or Least Squares Support Vector Machines) it is hard to analyze the influence of perturbed inputs on the ...
ICPR
2010
IEEE
13 years 11 months ago
2010
IEEE
This paper introduces a geometrically inspired large-margin classifier that can be a better alternative to the Support Vector Machines (SVMs) for the classification problems with ...
GFKL
2007
Springer
13 years 11 months ago
2007
Springer
In many classification applications, Support Vector Machines (SVMs) have proven to be highly performing and easy to handle classifiers with very good generalization abilities. Howe...
STOC
2010
ACM
13 years 11 months ago
2010
ACM
The spectral profile of a graph is a natural generalization of the classical notion of its Rayleigh quotient. Roughly speaking, given a graph G, for each 0 < < 1, the spect...