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» Optimization on Support Vector Machines
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SDM
2011
SIAM
232views Data Mining» more  SDM 2011»
14 years 1 months ago
A Sequential Dual Method for Structural SVMs
In many real world prediction problems the output is a structured object like a sequence or a tree or a graph. Such problems range from natural language processing to computationa...
Shirish Krishnaj Shevade, Balamurugan P., S. Sunda...
ICML
2008
IEEE
15 years 11 months ago
Modified MMI/MPE: a direct evaluation of the margin in speech recognition
In this paper we show how common speech recognition training criteria such as the Minimum Phone Error criterion or the Maximum Mutual Information criterion can be extended to inco...
Georg Heigold, Hermann Ney, Ralf Schlüter, Th...
ATS
2005
IEEE
100views Hardware» more  ATS 2005»
15 years 4 months ago
Finite State Machine Synthesis for At-Speed Oscillation Testability
In this paper, we propose an oscillation-based test methodology for sequential testing. This approach provides many advantages over traditional methods. (1) It is at-speed testing...
Katherine Shu-Min Li, Chung-Len Lee, Tagin Jiang, ...
GECCO
2006
Springer
162views Optimization» more  GECCO 2006»
15 years 2 months ago
Evolutionary learning with kernels: a generic solution for large margin problems
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
Ingo Mierswa
ICML
2008
IEEE
15 years 11 months ago
Large scale manifold transduction
We show how the regularizer of Transductive Support Vector Machines (TSVM) can be trained by stochastic gradient descent for linear models and multi-layer architectures. The resul...
Michael Karlen, Jason Weston, Ayse Erkan, Ronan Co...