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» Learning minimal abstractions
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VTS
2006
IEEE
108views Hardware» more  VTS 2006»
15 years 6 months ago
Bridging the Accuracy of Functional and Machine-Learning-Based Mixed-Signal Testing
Abstract— Numerous machine-learning-based test methodologies have been proposed in recent years as a fast alternative to the standard functional testing of mixed-signal/RF integr...
Haralampos-G. D. Stratigopoulos, Yiorgos Makris
93
Voted
ICML
2010
IEEE
15 years 1 months ago
Risk minimization, probability elicitation, and cost-sensitive SVMs
A new procedure for learning cost-sensitive SVM classifiers is proposed. The SVM hinge loss is extended to the cost sensitive setting, and the cost-sensitive SVM is derived as the...
Hamed Masnadi-Shirazi, Nuno Vasconcelos
103
Voted
AE
2007
Springer
15 years 6 months ago
Minimal and Necessary Conditions for the Emergence of Species-Specific Recognition Patterns
A simple mechanism is presented for the emergence of recognition patterns that are used by individuals to find each other and mate. The genetic component determines the brain of an...
Nicolas Brodu
99
Voted
ECML
2007
Springer
15 years 6 months ago
On Minimizing the Position Error in Label Ranking
Conventional classification learning allows a classifier to make a one shot decision in order to identify the correct label. However, in many practical applications, the problem ...
Eyke Hüllermeier, Johannes Fürnkranz
78
Voted
CAV
2008
Springer
110views Hardware» more  CAV 2008»
15 years 2 months ago
Monotonic Abstraction for Programs with Dynamic Memory Heaps
c Abstraction for Programs with Dynamic Memory Heaps Parosh Aziz Abdulla1 , Ahmed Bouajjani2 , Jonathan Cederberg1 , Fr
Parosh Aziz Abdulla, Ahmed Bouajjani, Jonathan Ced...