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» Analysing Randomized Distributed Algorithms
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PROMISE
2010
13 years 2 days ago
On the value of learning from defect dense components for software defect prediction
BACKGROUND: Defect predictors learned from static code measures can isolate code modules with a higher than usual probability of defects. AIMS: To improve those learners by focusi...
Hongyu Zhang, Adam Nelson, Tim Menzies
IUI
2011
ACM
12 years 8 months ago
ChemInk: a natural real-time recognition system for chemical drawings
We describe a new sketch recognition framework for chemical structure drawings that combines multiple levels of visual features using a jointly trained conditional random field. ...
Tom Y. Ouyang, Randall Davis