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ESANN
2007
13 years 7 months ago
The Intrinsic Recurrent Support Vector Machine
In this work, we present a new model for a Recurrent Support Vector Machine. We call it intrinsic because the complete recurrence is directly incorporated within the considered opt...
Daniel Schneegaß, Anton Maximilian Schä...
SDM
2007
SIAM
81views Data Mining» more  SDM 2007»
13 years 7 months ago
A PAC Bound for Approximate Support Vector Machines
We study a class of algorithms that speed up the training process of support vector machines (SVMs) by returning an approximate SVM. We focus on algorithms that reduce the size of...
Dongwei Cao, Daniel Boley
NIPS
1998
13 years 7 months ago
Using Analytic QP and Sparseness to Speed Training of Support Vector Machines
Training a Support Vector Machine (SVM) requires the solution of a very large quadratic programming (QP) problem. This paper proposes an algorithm for training SVMs: Sequential Mi...
John C. Platt
IPSN
2010
Springer
14 years 1 months ago
Consensus-based distributed linear support vector machines
This paper develops algorithms to train linear support vector machines (SVMs) when training data are distributed across different nodes and their communication to a centralized no...
Pedro A. Forero, Alfonso Cano, Georgios B. Giannak...
ICONIP
2007
13 years 7 months ago
Using Generalization Error Bounds to Train the Set Covering Machine
In this paper we eliminate the need for parameter estimation associated with the set covering machine (SCM) by directly minimizing generalization error bounds. Firstly, we consider...
Zakria Hussain, John Shawe-Taylor