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ECML
2004
Springer
15 years 10 months ago
Naive Bayesian Classifiers for Ranking
It is well-known that naive Bayes performs surprisingly well in classification, but its probability estimation is poor. In many applications, however, a ranking based on class prob...
Harry Zhang, Jiang Su
ERSA
2008
93views Hardware» more  ERSA 2008»
15 years 8 months ago
Multiparadigm Computing for Space-Based Synthetic Aperture Radar
Projected computational requirements for future space missions are outpacing technologies and trends in conventional embedded microprocessors. In order to meet the necessary levels...
Adam Jacobs, Grzegorz Cieslewski, Casey Reardon, A...
CONCURRENCY
1998
115views more  CONCURRENCY 1998»
15 years 6 months ago
Falcon: On-line monitoring for steering parallel programs
Abstract Advances in high performance computing, communications, and user interfaces enable developers to construct increasingly interactive high performance applications. The Falc...
Weiming Gu, Greg Eisenhauer, Karsten Schwan, Jeffr...
PAMI
2006
193views more  PAMI 2006»
15 years 6 months ago
A System for Learning Statistical Motion Patterns
Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, w...
Weiming Hu, Xuejuan Xiao, Zhouyu Fu, Dan Xie, Tien...
SIGIR
2008
ACM
15 years 6 months ago
Directly optimizing evaluation measures in learning to rank
One of the central issues in learning to rank for information retrieval is to develop algorithms that construct ranking models by directly optimizing evaluation measures used in i...
Jun Xu, Tie-Yan Liu, Min Lu, Hang Li, Wei-Ying Ma