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 ...
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...
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...
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 ...
— 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...