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ECCV
2008
Springer
14 years 9 months ago
Hierarchical Support Vector Random Fields: Joint Training to Combine Local and Global Features
Abstract. Recently, impressive results have been reported for the detection of objects in challenging real-world scenes. Interestingly however, the underlying models vary greatly e...
Paul Schnitzspan, Mario Fritz, Bernt Schiele
COLING
2002
13 years 7 months ago
Efficient Support Vector Classifiers for Named Entity Recognition
Named Entity (NE) recognition is a task in which proper nouns and numerical information are extracted from documents and are classified into categories such as person, organizatio...
Hideki Isozaki, Hideto Kazawa
ICDM
2009
IEEE
200views Data Mining» more  ICDM 2009»
13 years 5 months ago
Improving SVM Classification on Imbalanced Data Sets in Distance Spaces
Abstract--Imbalanced data sets present a particular challenge to the data mining community. Often, it is the rare event that is of interest and the cost of misclassifying the rare ...
Suzan Koknar-Tezel, Longin Jan Latecki
NIPS
2001
13 years 9 months ago
Kernel Logistic Regression and the Import Vector Machine
The support vector machine (SVM) is known for its good performance in binary classification, but its extension to multi-class classification is still an on-going research issue. I...
Ji Zhu, Trevor Hastie
CVPR
2008
IEEE
14 years 9 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