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» Evaluating algorithms that learn from data streams
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ICDE
2007
IEEE
206views Database» more  ICDE 2007»
16 years 1 months ago
Efficiently Processing Continuous k-NN Queries on Data Streams
Efficiently processing continuous k-nearest neighbor queries on data streams is important in many application domains, e. g. for network intrusion detection or in querysubscriber ...
Beng Chin Ooi, Christian Böhm, Claudia Plant,...
116
Voted
ITS
2010
Springer
178views Multimedia» more  ITS 2010»
15 years 5 months ago
Learning What Works in ITS from Non-traditional Randomized Controlled Trial Data
The traditional, well established approach to finding out what works in education research is to run a randomized controlled trial (RCT) using a standard pretest and posttest desig...
Zachary A. Pardos, Matthew D. Dailey, Neil T. Heff...
99
Voted
AVSS
2009
IEEE
15 years 7 months ago
Object-Video Streams for Preserving Privacy in Video Surveillance
—This paper presents a framework for preserving privacy in video surveillance. Raw video is decomposed into a background and one or more object-video streams. Objectvideo streams...
Faisal Z. Qureshi
141
Voted
PODS
2007
ACM
225views Database» more  PODS 2007»
16 years 21 days ago
Sketching unaggregated data streams for subpopulation-size queries
IP packet streams consist of multiple interleaving IP flows. Statistical summaries of these streams, collected for different measurement periods, are used for characterization of ...
Edith Cohen, Nick G. Duffield, Haim Kaplan, Carste...
94
Voted
ICDM
2007
IEEE
158views Data Mining» more  ICDM 2007»
15 years 7 months ago
On Appropriate Assumptions to Mine Data Streams: Analysis and Practice
Recent years have witnessed an increasing number of studies in stream mining, which aim at building an accurate model for continuously arriving data. Somehow most existing work ma...
Jing Gao, Wei Fan, Jiawei Han