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» Using Machine Learning to Support Debugging with Tarantula
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77
Voted
KDD
2010
ACM
175views Data Mining» more  KDD 2010»
15 years 6 months ago
Learning with cost intervals
Existing cost-sensitive learning methods work with unequal misclassification cost that is given by domain knowledge and appears as precise values. In many real-world applications,...
Xu-Ying Liu, Zhi-Hua Zhou
128
Voted
AAAI
1998
15 years 4 months ago
Learning to Extract Symbolic Knowledge from the World Wide Web
The World Wide Web is a vast source of information accessible to computers, but understandable only to humans. The goal of the research described here is to automatically create a...
Mark Craven, Dan DiPasquo, Dayne Freitag, Andrew M...
122
Voted
GECCO
2007
Springer
194views Optimization» more  GECCO 2007»
15 years 8 months ago
Hybrid coevolutionary algorithms vs. SVM algorithms
As a learning method support vector machine is regarded as one of the best classifiers with a strong mathematical foundation. On the other hand, evolutionary computational techniq...
Rui Li, Bir Bhanu, Krzysztof Krawiec
125
Voted
AAAI
2008
15 years 5 months ago
Learning and Inference with Constraints
Probabilistic modeling has been a dominant approach in Machine Learning research. As the field evolves, the problems of interest become increasingly challenging and complex. Makin...
Ming-Wei Chang, Lev-Arie Ratinov, Nicholas Rizzolo...
146
Voted
CVPR
2008
IEEE
16 years 4 months ago
Semi-supervised SVM batch mode active learning for image retrieval
Active learning has been shown as a key technique for improving content-based image retrieval (CBIR) performance. Among various methods, support vector machine (SVM) active learni...
Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R....