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DAGM
2004
Springer
15 years 7 months ago
MinOver Revisited for Incremental Support-Vector-Classification
The well-known and very simple MinOver algorithm is reformulated for incremental support vector classification with and without kernels. A modified proof for its O(t-1/2 ) converge...
Thomas Martinetz
CASC
2007
Springer
112views Mathematics» more  CASC 2007»
15 years 10 months ago
Polynomial Division Using Dynamic Arrays, Heaps, and Packed Exponent Vectors
A common way of implementing multivariate polynomial multiplication and division is to represent polynomials as linked lists of terms sorted in a term ordering and to use repeated ...
Michael B. Monagan, Roman Pearce
PR
2007
104views more  PR 2007»
15 years 3 months ago
Optimizing resources in model selection for support vector machine
Tuning SVM hyperparameters is an important step in achieving a high-performance learning machine. It is usually done by minimizing an estimate of generalization error based on the...
Mathias M. Adankon, Mohamed Cheriet
139
Voted
ICML
1998
IEEE
16 years 4 months ago
Feature Selection via Concave Minimization and Support Vector Machines
Computational comparison is made between two feature selection approaches for nding a separating plane that discriminates between two point sets in an n-dimensional feature space ...
Paul S. Bradley, Olvi L. Mangasarian
132
Voted
CORR
2006
Springer
78views Education» more  CORR 2006»
15 years 4 months ago
On the Fading Number of Multiple-Input Single-Output Fading Channels with Memory
We derive new upper and lower bounds on the fading number of multiple-input single-output (MISO) fading channels of general (not necessarily Gaussian) regular law with spatial and ...
Stefan M. Moser