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SDM
2007
SIAM
198views Data Mining» more  SDM 2007»
13 years 8 months ago
Learning from Time-Changing Data with Adaptive Windowing
We present a new approach for dealing with distribution change and concept drift when learning from data sequences that may vary with time. We use sliding windows whose size, inst...
Albert Bifet, Ricard Gavaldà
DCOSS
2007
Springer
14 years 1 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...
IICS
2009
Springer
13 years 12 months ago
Bi-directional Distribution of eLearning Content for Cross-technology Learning Communities
: This article describes the use of a service-oriented architecture to bridge the gap between different eLearning types and tools. The basic concept is a bi-directional distributio...
Raphael Zender, Enrico Dressler, Ulrike Lucke, Dja...
FLAIRS
2006
13 years 8 months ago
Decomposing Local Probability Distributions in Bayesian Networks for Improved Inference and Parameter Learning
A major difficulty in building Bayesian network models is the size of conditional probability tables, which grow exponentially in the number of parents. One way of dealing with th...
Adam Zagorecki, Mark Voortman, Marek J. Druzdzel
ITS
2000
Springer
159views Multimedia» more  ITS 2000»
13 years 11 months ago
Can We Learn from ITSs?
With the rise of VR, the internet, and mobile technologies and the shifts in educational focus from teaching to learning and from solitary to collaborative work, it's easy (bu...
Benedict du Boulay