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» Learning with Rigorous Support Vector Machines
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ICCV
2011
IEEE
14 years 6 months ago
Struck: Structured Output Tracking with Kernels
Adaptive tracking-by-detection methods are widely used in computer vision for tracking arbitrary objects. Current approaches treat the tracking problem as a classification task a...
Sam Hare, Amir Saffari, Philip H.S. Torr
NPL
2006
137views more  NPL 2006»
15 years 6 months ago
Minimal Structure of Self-Organizing HCMAC Neural Network Classifier
The authors previously proposed a self-organizing Hierarchical Cerebellar Model Articulation Controller (HCMAC) neural network containing a hierarchical GCMAC neural network and a ...
Chih-Ming Chen, Yung-Feng Lu, Chin-Ming Hong
FLAIRS
2008
15 years 9 months ago
A Semantic Feature for Verbal Predicate and Semantic Role Labeling Using SVMs
This paper shows that semantic role labeling is a consequence of accurate verbal predicate labeling. In doing so, the paper presents a novel type of semantic feature for verbal pr...
Hansen A. Schwartz, Fernando Gomez, Christopher Mi...
JMLR
2006
116views more  JMLR 2006»
15 years 6 months ago
Step Size Adaptation in Reproducing Kernel Hilbert Space
This paper presents an online support vector machine (SVM) that uses the stochastic meta-descent (SMD) algorithm to adapt its step size automatically. We formulate the online lear...
S. V. N. Vishwanathan, Nicol N. Schraudolph, Alex ...
IJCNN
2007
IEEE
16 years 1 months ago
Preference Learning for Category-Ranking based Interactive Text Categorization
— Category Ranking is a variant of the multi-label classification problem, in which, rather than performing a (hard) assignment to an object of categories from a predefined set...
Fabio Aiolli, Fabrizio Sebastiani, Alessandro Sper...