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» Can Document Selection Help Semi-supervised Learning
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KDD
2007
ACM
139views Data Mining» more  KDD 2007»
14 years 10 months ago
Raising the baseline for high-precision text classifiers
Many important application areas of text classifiers demand high precision and it is common to compare prospective solutions to the performance of Naive Bayes. This baseline is us...
Aleksander Kolcz, Wen-tau Yih
CVPR
2006
IEEE
14 years 12 months ago
Joint Boosting Feature Selection for Robust Face Recognition
A fundamental challenge in face recognition lies in determining what facial features are important for the identification of faces. In this paper, a novel face recognition framewo...
Rong Xiao, Wu-Jun Li, Yuandong Tian, Xiaoou Tang
ERCIMDL
2003
Springer
91views Education» more  ERCIMDL 2003»
14 years 3 months ago
Search Engine-Crawler Symbiosis: Adapting to Community Interests
Web crawlers have been used for nearly a decade as a search engine component to create and update large collections of documents. Typically the crawler and the rest of the search e...
Gautam Pant, Shannon Bradshaw, Filippo Menczer
CVPR
2007
IEEE
14 years 12 months ago
Combining Static Classifiers and Class Syntax Models for Logical Entity Recognition in Scanned Historical Documents
Class syntax can be used to 1) model temporal or locational evolvement of class labels of feature observation sequences, 2) correct classification errors of static classifiers if ...
Song Mao, Praveer Mansukhani, George R. Thoma
AAAI
1994
13 years 11 months ago
Automated Postediting of Documents
Large amounts of low- to medium-quality English texts are now being produced by machine translation (MT) systems, optical character readers (OCR), and non-native speakers of Engli...
Kevin Knight, Ishwar Chander