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ICML
2003
IEEE
14 years 8 months ago
Margin Distribution and Learning
Recent theoretical results have shown that improved bounds on generalization error of classifiers can be obtained by explicitly taking the observed margin distribution of the trai...
Ashutosh Garg, Dan Roth
FSTTCS
2004
Springer
14 years 23 days ago
Testing Geometric Convexity
We consider the problem of determining whether a given set S in Rn is approximately convex, i.e., if there is a convex set K ∈ Rn such that the volume of their symmetric differe...
Luis Rademacher, Santosh Vempala
CORR
2010
Springer
148views Education» more  CORR 2010»
13 years 2 months ago
A Unifying View of Multiple Kernel Learning
Recent research on multiple kernel learning has lead to a number of approaches for combining kernels in regularized risk minimization. The proposed approaches include different for...
Marius Kloft, Ulrich Rückert, Peter L. Bartle...
TNN
2008
182views more  TNN 2008»
13 years 7 months ago
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...
Ivor Wai-Hung Tsang, András Kocsor, James T...
ICASSP
2009
IEEE
14 years 2 months ago
A complex cross-spectral distribution model using Normal Variance Mean Mixtures
We propose a model for the density of cross-spectral coefficients using Normal Variance Mean Mixtures. We show that this model density generalizes the corresponding marginal dens...
Jason A. Palmer, Scott Makeig, Kenneth Kreutz-Delg...