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» Robustness of Classifiers to Changing Environments
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AAAI
2010
13 years 9 months ago
A Layered Approach to People Detection in 3D Range Data
People tracking is a key technology for autonomous systems, intelligent cars and social robots operating in populated environments. What makes the task difficult is that the appea...
Luciano Spinello, Kai Oliver Arras, Rudolph Triebe...
ALT
2010
Springer
13 years 9 months ago
Contrast Pattern Mining and Its Application for Building Robust Classifiers
: The ability to distinguish, differentiate and contrast between different data sets is a key objective in data mining. Such ability can assist domain experts to understand their d...
Kotagiri Ramamohanarao
CCS
2009
ACM
14 years 2 months ago
Keep your friends close: the necessity for updating an anomaly sensor with legitimate environment changes
Large-scale distributed systems have dense, complex code-bases that are assumed to perform multiple and inter-dependent tasks while user interaction is present. The way users inte...
Angelos Stavrou, Gabriela F. Cretu-Ciocarlie, Mich...
CORR
2011
Springer
171views Education» more  CORR 2011»
13 years 2 months ago
Persistent Robotic Tasks: Monitoring and Sweeping in Changing Environments
—We present controllers that enable mobile robots to persistently monitor or sweep a changing environment. The changing environment is modeled as a field which grows in location...
Stephen L. Smith, Mac Schwager, Daniela Rus
ICPR
2008
IEEE
14 years 9 months ago
Incremental learning in non-stationary environments with concept drift using a multiple classifier based approach
We outline an incremental learning algorithm designed for nonstationary environments where the underlying data distribution changes over time. With each dataset drawn from a new e...
Matthew T. Karnick, Michael Muhlbaier, Robi Polika...