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ICDM
2010
IEEE
199views Data Mining» more  ICDM 2010»
14 years 7 months ago
Addressing Concept-Evolution in Concept-Drifting Data Streams
Abstract--The problem of data stream classification is challenging because of many practical aspects associated with efficient processing and temporal behavior of the stream. Two s...
Mohammad M. Masud, Qing Chen, Latifur Khan, Charu ...
CIKM
2006
Springer
15 years 1 months ago
Adaptive non-linear clustering in data streams
Data stream clustering has emerged as a challenging and interesting problem over the past few years. Due to the evolving nature, and one-pass restriction imposed by the data strea...
Ankur Jain, Zhihua Zhang, Edward Y. Chang
ICDCS
1999
IEEE
15 years 2 months ago
Run-time Detection in Parallel and Distributed Systems: Application to Safety-Critical Systems
There is growing interest in run-time detection as parallel and distributed systems grow larger and more complex. This work targets run-time analysis of complex, interactive scien...
Beth Plale, Karsten Schwan
PAKDD
2010
ACM
165views Data Mining» more  PAKDD 2010»
14 years 11 months ago
Classification and Novel Class Detection in Data Streams with Active Mining
We present ActMiner, which addresses four major challenges to data stream classification, namely, infinite length, concept-drift, conceptevolution, and limited labeled data. Most o...
Mohammad M. Masud, Jing Gao, Latifur Khan, Jiawei ...
CLUSTER
2007
IEEE
15 years 4 months ago
Anomaly localization in large-scale clusters
— A critical problem facing by managing large-scale clusters is to identify the location of problems in a system in case of unusual events. As the scale of high performance compu...
Ziming Zheng, Yawei Li, Zhiling Lan