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» Learning with Constrained and Unlabelled Data
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JCST
2011
89views more  JCST 2011»
13 years 4 months ago
Software Defect Detection with Rocus
Software defect detection aims to automatically identify defective software modules for efficient software test in order to improve the quality of a software system. Although many...
Yuan Jiang, Ming Li, Zhi-Hua Zhou
ICML
2004
IEEE
14 years 10 months ago
Semi-supervised learning using randomized mincuts
In many application domains there is a large amount of unlabeled data but only a very limited amount of labeled training data. One general approach that has been explored for util...
Avrim Blum, John D. Lafferty, Mugizi Robert Rweban...
SDM
2003
SIAM
156views Data Mining» more  SDM 2003»
13 years 11 months ago
Detection of Underrepresented Biological Sequences using Class-Conditional Distribution Models
A labeled sequence data set related to a certain biological property is often biased and, therefore, does not completely capture its diversity in nature. To reduce this sampling b...
Slobodan Vucetic, Dragoljub Pokrajac, Hongbo Xie, ...
PAKDD
2007
ACM
184views Data Mining» more  PAKDD 2007»
14 years 4 months ago
Exploring Group Moving Pattern for an Energy-Constrained Object Tracking Sensor Network
In this paper, we investigate and utilize the characteristic of the group movement of objects to achieve energy conservation in the inherently resource-constrained wireless object ...
Hsiao-Ping Tsai, De-Nian Yang, Wen-Chih Peng, Ming...
CVPR
2009
IEEE
15 years 5 months ago
What's It Going to Cost You?: Predicting Effort vs. Informativeness for Multi-Label Image Annotations
Active learning strategies can be useful when manual labeling effort is scarce, as they select the most informative examples to be annotated first. However, for visual category ...
Sudheendra Vijayanarasimhan (University of Texas a...