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» Robustness of Classifiers to Changing Environments
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CBMS
2008
IEEE
13 years 9 months ago
Effectiveness of Local Feature Selection in Ensemble Learning for Prediction of Antimicrobial Resistance
In the real world concepts are often not stable but change over time. A typical example of this in the biomedical context is antibiotic resistance, where pathogen sensitivity may ...
Seppo Puuronen, Mykola Pechenizkiy, Alexey Tsymbal
PPSN
2010
Springer
13 years 5 months ago
Environment-Driven Embodied Evolution in a Population of Autonomous Agents
This paper is concerned with a fixed-size population of autonomous agents facing unknown, possibly changing, environments. The motivation is to design an embodied evolutionary algo...
Nicolas Bredeche, Jean-Marc Montanier
ICASSP
2011
IEEE
12 years 11 months ago
Efficient convex optimization for real-time robust beamforming with microphone arrays
This paper presents an efficient implementation of a robust adaptive beamforming algorithm based on convex optimization for applications in the processing-constrained environment...
Eric A. Durant, Ivo Merks, Bill Woods, Jinjun Xiao...
IJCNN
2006
IEEE
14 years 1 months ago
A computational intelligence-based criterion to detect non-stationarity trends
—The stationarity hypothesis is largely and implicitly assumed when designing classifiers (especially those for industrial applications) but it does not generally hold in practic...
Cesare Alippi, Manuel Roveri
DATE
2010
IEEE
154views Hardware» more  DATE 2010»
13 years 8 months ago
Computing robustness of FlexRay schedules to uncertainties in design parameters
Abstract--In the current environment of rapidly changing invehicle requirements and ever-increasing functional content for automotive EE systems, there are several sources of uncer...
Arkadeb Ghosal, Haibo Zeng, Marco Di Natale, Yakov...