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ASIAN
2005
Springer
130views Algorithms» more  ASIAN 2005»
15 years 8 months ago
A Hybrid Method for Detecting Data Stream Changes with Complex Semantics in Intensive Care Unit
Abstract. Detecting changes in data streams is very important for many applications. This paper presents a hybrid method for detecting data stream changes in intensive care unit. I...
Ting Yin, Hongyan Li, Zijing Hu, Yu Fan, Jianlong ...
ASC
2011
15 years 1 months ago
Handling drifts and shifts in on-line data streams with evolving fuzzy systems
In this paper, we present new approaches to handling drift and shift in on-line data streams with the help of evolving fuzzy systems (EFS), which are characterized by the fact tha...
Edwin Lughofer, Plamen P. Angelov
ISI
2008
Springer
15 years 4 months ago
Anomaly detection in high-dimensional network data streams: A case study
In this paper, we study the problem of anomaly detection in high-dimensional network streams. We have developed a new technique, called Stream Projected Ouliter deTector (SPOT), t...
Ji Zhang, Qigang Gao, Hai H. Wang
ASPLOS
2006
ACM
16 years 4 days ago
Exploiting coarse-grained task, data, and pipeline parallelism in stream programs
As multicore architectures enter the mainstream, there is a pressing demand for high-level programming models that can effectively map to them. Stream programming offers an attrac...
Michael I. Gordon, William Thies, Saman P. Amarasi...
PRL
2010
158views more  PRL 2010»
15 years 4 months ago
Data clustering: 50 years beyond K-means
: Organizing data into sensible groupings is one of the most fundamental modes of understanding and learning. As an example, a common scheme of scientific classification puts organ...
Anil K. Jain