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JCB
2002
70views more  JCB 2002»
14 years 9 months ago
Strong Feature Sets from Small Samples
For small samples, classi er design algorithms typically suffer from over tting. Given a set of features, a classi er must be designed and its error estimated. For small samples, ...
Seungchan Kim, Edward R. Dougherty, Junior Barrera...
NAR
2007
91views more  NAR 2007»
14 years 9 months ago
SuperHapten: a comprehensive database for small immunogenic compounds
The immune system protects organisms from foreign proteins, peptide epitopes and a multitude of chemical compounds. Among these, haptens are small molecules, eliciting an immune r...
Stefan Günther, Dorothea Hempel, Mathias Dunk...
MM
2005
ACM
172views Multimedia» more  MM 2005»
15 years 3 months ago
Learning the semantics of multimedia queries and concepts from a small number of examples
In this paper we unify two supposedly distinct tasks in multimedia retrieval. One task involves answering queries with a few examples. The other involves learning models for seman...
Apostol Natsev, Milind R. Naphade, Jelena Tesic
WWW
2009
ACM
15 years 4 months ago
Bootstrapped extraction of class attributes
As an alternative to previous studies on extracting class attributes from unstructured text, which consider either Web documents or query logs as the source of textual data, A boo...
Joseph Reisinger, Marius Pasca
MICAI
2007
Springer
15 years 4 months ago
Taking Advantage of the Web for Text Classification with Imbalanced Classes
A problem of supervised approaches for text classification is that they commonly require high-quality training data to construct an accurate classifier. Unfortunately, in many real...
Rafael Guzmán-Cabrera, Manuel Montes-y-G&oa...