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» Learning Models for Predicting Recognition Performance
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DIS
2005
Springer
15 years 8 months ago
Exploring Predicate-Argument Relations for Named Entity Recognition in the Molecular Biology Domain
In this paper, the semantic relationships between a predicate and its arguments in terms of semantic roles are employed to improve lexical-based named entity recognition (NER) in t...
Tuangthong Wattarujeekrit, Nigel Collier
BIOINFORMATICS
2005
140views more  BIOINFORMATICS 2005»
15 years 3 months ago
Profile-based direct kernels for remote homology detection and fold recognition
Motivation: Remote homology detection between protein sequences is a central problem in computational biology. Supervised learning algorithms based on support vector machines are ...
Huzefa Rangwala, George Karypis
TIP
2011
137views more  TIP 2011»
14 years 9 months ago
Boosting Color Feature Selection for Color Face Recognition
—This paper introduces the new color face recognition (FR) method that makes effective use of boosting learning as color-component feature selection framework. The proposed boost...
Jae Young Choi, Yong Man Ro, Konstantinos N. Plata...
ECCV
2008
Springer
16 years 5 months ago
Learning to Localize Objects with Structured Output Regression
Sliding window classifiers are among the most successful and widely applied techniques for object localization. However, training is typically done in a way that is not specific to...
Matthew B. Blaschko, Christoph H. Lampert
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
16 years 3 months ago
Practical learning from one-sided feedback
In many data mining applications, online labeling feedback is only available for examples which were predicted to belong to the positive class. Such applications include spam filt...
D. Sculley