364 search results - page 2 / 73 » On the generalization of soft margin algorithms |
ICPR
2008
IEEE
14 years 8 months ago
2008
IEEE
The classification performance of nearest prototype classifiers largely relies on the prototype learning algorithms, such as the learning vector quantization (LVQ) and the minimum...
NIPS
2007
13 years 8 months ago
2007
We present a novel boosting algorithm, called SoftBoost, designed for sets of binary labeled examples that are not necessarily separable by convex combinations of base hypotheses....
ICML
2010
IEEE
13 years 5 months ago
2010
IEEE
We introduce into the classical Perceptron algorithm with margin a mechanism of unlearning which in the course of the regular update allows for a reduction of possible contributio...
ICASSP
2011
IEEE
12 years 10 months ago
2011
IEEE
—Discriminative Training (DT) methods for acoustic modeling, such as MMI, MCE, and SVM, have been proved effective in speaker recognition. In this paper we propose a DT method fo...
ALT
2008
Springer
14 years 4 months ago
2008
Springer
In this paper we discuss boosting algorithms that maximize the soft margin of the produced linear combination of base hypotheses. LPBoost is the most straightforward boosting algor...