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» Evaluating algorithms that learn from data streams
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ICDCSW
2007
IEEE
15 years 10 months ago
Group-aware Stream Filtering
In this paper we are concerned with disseminating high-volume data streams to many simultaneous context-aware applications over a low-bandwidth wireless mesh network. For bandwidt...
Ming Li, David Kotz
CVPR
2006
IEEE
16 years 6 months ago
Meta-Evaluation of Image Segmentation Using Machine Learning
Image segmentation is a fundamental step in many computer vision applications. Generally, the choice of a segmentation algorithm, or parameterization of a given algorithm, is sele...
Hui Zhang, Sharath R. Cholleti, Sally A. Goldman, ...
CORR
2007
Springer
172views Education» more  CORR 2007»
15 years 4 months ago
A Data-Parallel Version of Aleph
This is to present work on modifying the Aleph ILP system so that it evaluates the hypothesised clauses in parallel by distributing the data-set among the nodes of a parallel or di...
Stasinos Konstantopoulos
ICDE
2008
IEEE
137views Database» more  ICDE 2008»
16 years 5 months ago
Stop Chasing Trends: Discovering High Order Models in Evolving Data
Abstract-- Many applications are driven by evolving data -patterns in web traffic, program execution traces, network event logs, etc., are often non-stationary. Building prediction...
Shixi Chen, Haixun Wang, Shuigeng Zhou, Philip S. ...
ICDM
2006
IEEE
119views Data Mining» more  ICDM 2006»
15 years 10 months ago
Fast On-line Kernel Learning for Trees
Kernel methods have been shown to be very effective for applications requiring the modeling of structured objects. However kernels for structures usually are too computational dem...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...