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» Co-Tracking Using Semi-Supervised Support Vector Machines
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121
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RECOMB
2007
Springer
16 years 2 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...
114
Voted
ANNS
2007
15 years 4 months ago
Direct and indirect classification of high-frequency LNA performance using machine learning techniques
The task of determining low noise amplifier (LNA) high-frequency performance in functional testing is as challenging as designing the circuit itself due to the difficulties associa...
Peter C. Hung, Seán F. McLoone, Magdalena S...
94
Voted
CVPR
2008
IEEE
16 years 4 months 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
115
Voted
ICMCS
2005
IEEE
148views Multimedia» more  ICMCS 2005»
15 years 8 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
123
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ECML
2004
Springer
15 years 8 months ago
Experiments in Value Function Approximation with Sparse Support Vector Regression
Abstract. We present first experiments using Support Vector Regression as function approximator for an on-line, sarsa-like reinforcement learner. To overcome the batch nature of S...
Tobias Jung, Thomas Uthmann