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» Adaptive Learning from Evolving Data Streams
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IJCNN
2006
IEEE
14 years 1 months ago
Nominal-scale Evolving Connectionist Systems
— A method is presented for extending the Evolving Connectionist System (ECoS) algorithm that allows it to explicitly represent and learn nominal-scale data without the need for ...
Michael J. Watts
SIGMOD
2004
ACM
209views Database» more  SIGMOD 2004»
14 years 7 months ago
MAIDS: Mining Alarming Incidents from Data Streams
Real-time surveillance systems, network and telecommunication systems, and other dynamic processes often generate tremendous (potentially infinite) volume of stream data. Effectiv...
Y. Dora Cai, David Clutter, Greg Pape, Jiawei Han,...
EUROGP
2010
Springer
166views Optimization» more  EUROGP 2010»
14 years 15 days ago
Learning a Lot from Only a Little: Genetic Programming for Panel Segmentation on Sparse Sensory Evaluation Data
We describe a data mining framework that derives panelist information from sparse flavour survey data. One component of the framework executes genetic programming ensemble based s...
Katya Vladislavleva, Kalyan Veeramachaneni, Una-Ma...
IPCCC
2007
IEEE
14 years 1 months ago
Streaming in MANET: Proactive Link Protection and Receiver-Oriented Adaptation
Multimedia streaming applications can significantly boost the value of mobile ad hoc networks (MANET). Live streaming, however, means continuous data delivery, which is a major c...
Toby Xu, Ymg Cai
ICTAI
2007
IEEE
14 years 1 months ago
An Adaptive Distributed Ensemble Approach to Mine Concept-Drifting Data Streams
An adaptive boosting ensemble algorithm for classifying homogeneous distributed data streams is presented. The method builds an ensemble of classifiers by using Genetic Programmi...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...