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» Co-Tracking Using Semi-Supervised Support Vector Machines
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BMCBI
2010
130views more  BMCBI 2010»
15 years 6 months ago
Amino acid "little Big Bang": Representing amino acid substitution matrices as dot products of Euclidian vectors
Background: Sequence comparisons make use of a one-letter representation for amino acids, the necessary quantitative information being supplied by the substitution matrices. This ...
Karel Zimmermann, Jean-François Gibrat
ICANN
2007
Springer
16 years 13 days ago
Selection of Basis Functions Guided by the L2 Soft Margin
Support Vector Machines (SVMs) for classification tasks produce sparse models by maximizing the margin. Two limitations of this technique are considered in this work: firstly, th...
Ignacio Barrio, Enrique Romero, Lluís Belan...
ICANN
2007
Springer
15 years 10 months ago
Resilient Approximation of Kernel Classifiers
Abstract. Trained support vector machines (SVMs) have a slow runtime classification speed if the classification problem is noisy and the sample data set is large. Approximating the...
Thorsten Suttorp, Christian Igel
ICASSP
2011
IEEE
14 years 10 months ago
Dynamics of tongue gestures extracted automatically from ultrasound
We describe a system for automatically extracting dynamics of tongue gestures from ultrasound images of the tongue using translational deep belief networks (tDBNs). In tDBNs, a jo...
Jeff Berry, Ian Fasel
PPOPP
1993
ACM
15 years 10 months ago
Experience with Fine-Grain Synchronization in MIMD Machines for Preconditioned Conjugate Gradient
This paper discusses our experience with fine-grain synchronization for a variant of the preconditioned conjugate gradient method. This algorithm represents a large class of algo...
Donald Yeung, Anant Agarwal