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» Competitive Analysis of Distributed Algorithms
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128
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PAKDD
2000
ACM
161views Data Mining» more  PAKDD 2000»
15 years 4 months ago
Adaptive Boosting for Spatial Functions with Unstable Driving Attributes
Combining multiple global models (e.g. back-propagation based neural networks) is an effective technique for improving classification accuracy by reducing a variance through manipu...
Aleksandar Lazarevic, Tim Fiez, Zoran Obradovic
106
Voted
AIPS
2000
15 years 2 months ago
Planning with Incomplete Information as Heuristic Search in Belief Space
The formulation of planning as heuristic search with heuristics derived from problem representations has turned out to be a fruitful approach for classical planning. In this paper...
Blai Bonet, Hector Geffner
94
Voted
JUCS
2008
122views more  JUCS 2008»
15 years 17 days ago
Using an Evolving Thematic Clustering in a Text Segmentation Process
Abstract: The thematic text segmentation task consists in identifying the most important thematic breaks in a document in order to cut it into homogeneous passages. We propose in t...
Sylvain Lamprier, Tassadit Amghar, Bernard Levrat,...
TIP
2008
175views more  TIP 2008»
15 years 15 days ago
Customizing Kernel Functions for SVM-Based Hyperspectral Image Classification
Previous research applying kernel methods such as support vector machines (SVMs) to hyperspectral image classification has achieved performance competitive with the best available ...
Baofeng Guo, Steve R. Gunn, Robert I. Damper, Jame...
108
Voted
CIKM
2010
Springer
14 years 11 months ago
Partial drift detection using a rule induction framework
The major challenge in mining data streams is the issue of concept drift, the tendency of the underlying data generation process to change over time. In this paper, we propose a g...
Damon Sotoudeh, Aijun An