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» Semi-Supervised Support Vector Machines
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NIPS
2000
13 years 11 months ago
A Support Vector Method for Clustering
We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
Asa Ben-Hur, David Horn, Hava T. Siegelmann, Vladi...
ML
2008
ACM
162views Machine Learning» more  ML 2008»
13 years 10 months ago
Incorporating prior knowledge in support vector regression
This paper explores the addition of constraints to the linear programming formulation of the support vector regression problem for the incorporation of prior knowledge. Equality an...
Fabien Lauer, Gérard Bloch
RECOMB
2007
Springer
14 years 10 months ago
Support Vector Training of Protein Alignment Models
Abstract. Sequence to structure alignment is an important step in homology modeling of protein structures. Incorporation of features like secondary structure, solvent accessibility...
Chun-Nam John Yu, Thorsten Joachims, Ron Elber, Ja...
CVPR
2008
IEEE
15 years 4 days ago
Enforcing non-positive weights for stable support vector tracking
In this paper we demonstrate that the support vector tracking (SVT) framework first proposed by Avidan is equivalent to the canonical Lucas-Kanade (LK) algorithm with a weighted E...
Simon Lucey
ICMCS
2005
IEEE
148views Multimedia» more  ICMCS 2005»
14 years 3 months ago
Facial Expression Recognition with Relevance Vector Machines
For many decades automatic facial expression recognition has scientifically been considered a real challenging problem in the fields of pattern recognition or robotic vision. The ...
Dragos Datcu, Léon J. M. Rothkrantz