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» Evaluating algorithms that learn from data streams
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SDM
2009
SIAM
119views Data Mining» more  SDM 2009»
15 years 7 months ago
Twin Vector Machines for Online Learning on a Budget.
This paper proposes Twin Vector Machine (TVM), a constant space and sublinear time Support Vector Machine (SVM) algorithm for online learning. TVM achieves its favorable scaling b...
Zhuang Wang, Slobodan Vucetic
MOBIDE
2010
ACM
14 years 10 months ago
Power-aware operator placement and broadcasting of continuous query results
Complex event detection over data streams has become ubiquitous through the widespread use of sensors, wireless connectivity and the wide variety of end-user mobile devices. Typic...
Panayiotis Neophytou, Mohamed A. Sharaf, Panos K. ...
100
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IDA
2005
Springer
15 years 3 months ago
Learning from Ambiguously Labeled Examples
Inducing a classification function from a set of examples in the form of labeled instances is a standard problem in supervised machine learning. In this paper, we are concerned w...
Eyke Hüllermeier, Jürgen Beringer
DCOSS
2007
Springer
15 years 4 months ago
Separating the Wheat from the Chaff: Practical Anomaly Detection Schemes in Ecological Applications of Distributed Sensor Networ
Abstract. We develop a practical, distributed algorithm to detect events, identify measurement errors, and infer missing readings in ecological applications of wireless sensor netw...
Luís M. A. Bettencourt, Aric A. Hagberg, Le...
DEBS
2008
ACM
14 years 12 months ago
Event dissemination via group-aware stream filtering
We consider a distributed system that disseminates highvolume event streams to many simultaneous monitoring applications over a low-bandwidth network. For bandwidth efficiency, we...
Ming Li, David Kotz