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COLT
2003
Springer
14 years 27 days ago
Learning with Rigorous Support Vector Machines
We examine the so-called rigorous support vector machine (RSVM) approach proposed by Vapnik (1998). The formulation of RSVM is derived by explicitly implementing the structural ris...
Jinbo Bi, Vladimir Vapnik
DAGM
2004
Springer
13 years 11 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
NIPS
2004
13 years 9 months ago
Support Vector Classification with Input Data Uncertainty
This paper investigates a new learning model in which the input data is corrupted with noise. We present a general statistical framework to tackle this problem. Based on the stati...
Jinbo Bi, Tong Zhang
NAACL
2001
13 years 9 months ago
Chunking with Support Vector Machines
We apply Support Vector Machines (SVMs) to identify English base phrases (chunks). SVMs are known to achieve high generalization performance even with input data of high dimension...
Taku Kudo, Yuji Matsumoto
ESANN
2000
13 years 9 months ago
Algorithmic approaches to training Support Vector Machines: a survey
: Support Vector Machines (SVMs) have become an increasingly popular tool for machine learning tasks involving classi cation, regression or novelty detection. They exhibit good gen...
Colin Campbell