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» Evaluating algorithms that learn from data streams
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EDM
2010
145views Data Mining» more  EDM 2010»
15 years 2 months ago
Mining Rare Association Rules from e-Learning Data
Rare association rules are those that only appear infrequently even though they are highly associated with very specific data. In consequence, these rules can be very appropriate f...
Cristóbal Romero, José Raúl R...
NOSSDAV
2009
Springer
15 years 7 months ago
SLIPstream: scalable low-latency interactive perception on streaming data
A critical problem in implementing interactive perception applications is the considerable computational cost of current computer vision and machine learning algorithms, which typ...
Padmanabhan Pillai, Lily B. Mummert, Steven W. Sch...
PVLDB
2010
134views more  PVLDB 2010»
14 years 11 months ago
Conditioning and Aggregating Uncertain Data Streams: Going Beyond Expectations
Uncertain data streams are increasingly common in real-world deployments and monitoring applications require the evaluation of complex queries on such streams. In this paper, we c...
Thanh T. L. Tran, Andrew McGregor, Yanlei Diao, Li...
UAI
2008
15 years 2 months ago
Learning Inclusion-Optimal Chordal Graphs
Chordal graphs can be used to encode dependency models that are representable by both directed acyclic and undirected graphs. This paper discusses a very simple and efficient algo...
Vincent Auvray, Louis Wehenkel
MCS
2005
Springer
15 years 6 months ago
Ensembles of Classifiers from Spatially Disjoint Data
We describe an ensemble learning approach that accurately learns from data that has been partitioned according to the arbitrary spatial requirements of a large-scale simulation whe...
Robert E. Banfield, Lawrence O. Hall, Kevin W. Bow...