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154
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ACL
2008
15 years 5 months ago
Exploiting Feature Hierarchy for Transfer Learning in Named Entity Recognition
We present a novel hierarchical prior structure for supervised transfer learning in named entity recognition, motivated by the common structure of feature spaces for this task acr...
Andrew Arnold, Ramesh Nallapati, William W. Cohen
120
Voted
SIGIR
2008
ACM
15 years 3 months ago
Semi-supervised spam filtering: does it work?
The results of the 2006 ECML/PKDD Discovery Challenge suggest that semi-supervised learning methods work well for spam filtering when the source of available labeled examples diff...
Mona Mojdeh, Gordon V. Cormack
ISBI
2009
IEEE
15 years 10 months ago
Quantitative Comparison of Spot Detection Methods in Live-Cell Fluorescence Microscopy Imaging
In live-cell fluorescence microscopy imaging, quantitative analysis of biological image data generally involves the detection of many subresolution objects, appearing as diffract...
Ihor Smal, Marco Loog, Wiro J. Niessen, Erik H. W....
KDD
2004
ACM
624views Data Mining» more  KDD 2004»
15 years 8 months ago
Programming the K-means clustering algorithm in SQL
Using SQL has not been considered an efficient and feasible way to implement data mining algorithms. Although this is true for many data mining, machine learning and statistical a...
Carlos Ordonez
122
Voted
JMLR
2010
172views more  JMLR 2010»
14 years 10 months ago
Modeling annotator expertise: Learning when everybody knows a bit of something
Supervised learning from multiple labeling sources is an increasingly important problem in machine learning and data mining. This paper develops a probabilistic approach to this p...
Yan Yan, Rómer Rosales, Glenn Fung, Mark W....