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» Evaluating algorithms that learn from data streams
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KDD
2009
ACM
168views Data Mining» more  KDD 2009»
15 years 10 months ago
Sustainable operation and management of data center chillers using temporal data mining
Motivation: Data centers are a critical component of modern IT infrastructure but are also among the worst environmental offenders through their increasing energy usage and the re...
Debprakash Patnaik, Manish Marwah, Ratnesh K. Shar...
134
Voted
CVPR
2009
IEEE
16 years 5 months ago
A Streaming Framework for Seamless Building Reconstruction from Large-Scale Aerial LiDAR Data
We present a streaming framework for seamless building reconstruction from huge aerial LiDAR point sets. By storing data as stream files on hard disk and using main memory as only ...
Qian-Yi Zhou (University of Southern California), ...
88
Voted
GECCO
2000
Springer
106views Optimization» more  GECCO 2000»
15 years 1 months ago
A Genetic Segmentation Algorithm for Image Data Streams and Video
We describe a genetic segmentation algorithm for image data streams and video. This algorithm operates on segments of a string representation. It is similar to both classical gene...
Patrick Chiu, Andreas Girgensohn, Wolfgang Polak, ...
131
Voted
ICDM
2007
IEEE
301views Data Mining» more  ICDM 2007»
15 years 2 months ago
Stream Event Detection: A Unified Framework for Mining Outlier, Change and Burst Simultaneously over Data Stream
Event detection is one of the most important issues of event processing system, especially Complex Event Processing (CEP). Outlier event, change event and burst event are three ty...
Zhijian Yuan, Kai Du, Yan Jia, Jiajia Miao
ICDM
2007
IEEE
254views Data Mining» more  ICDM 2007»
15 years 4 months ago
Sampling for Sequential Pattern Mining: From Static Databases to Data Streams
Sequential pattern mining is an active field in the domain of knowledge discovery. Recently, with the constant progress in hardware technologies, real-world databases tend to gro...
Chedy Raïssi, Pascal Poncelet