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» Learning Functions from Imperfect Positive Data
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CIKM
2009
Springer
14 years 3 months ago
Incremental query evaluation for support vector machines
Support vector machines (SVMs) have been widely used in multimedia retrieval to learn a concept in order to find the best matches. In such a SVM active learning environment, the ...
Danzhou Liu, Kien A. Hua
BMCBI
2011
13 years 10 days ago
A mutation degree model for the identification of transcriptional regulatory elements
Background: Current approaches for identifying transcriptional regulatory elements are mainly via the combination of two properties, the evolutionary conservation and the overrepr...
Changqing Zhang, Jin Wang, Xu Hua, Jinggui Fang, H...
SIGMOD
2006
ACM
122views Database» more  SIGMOD 2006»
14 years 9 months ago
MonetDB/XQuery: a fast XQuery processor powered by a relational engine
Relational XQuery systems try to re-use mature relational data management infrastructures to create fast and scalable XML database technology. This paper describes the main featur...
Peter A. Boncz, Torsten Grust, Maurice van Keulen,...
ICML
2010
IEEE
13 years 9 months ago
Large Scale Max-Margin Multi-Label Classification with Priors
We propose a max-margin formulation for the multi-label classification problem where the goal is to tag a data point with a set of pre-specified labels. Given a set of L labels, a...
Bharath Hariharan, Lihi Zelnik-Manor, S. V. N. Vis...
ICCV
2009
IEEE
15 years 1 months ago
Decomposing a Scene into Geometric and Semantically Consistent Regions
High-level, or holistic, scene understanding involves reasoning about objects, regions, and the 3D relationships between them. This requires a representation above the level of ...
Stephen Gould, Richard Fulton, Daphne Koller