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ASIAN
2005
Springer
130views Algorithms» more  ASIAN 2005»
15 years 6 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
14 years 11 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 3 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
125
Voted
ASPLOS
2006
ACM
15 years 10 months 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...
152
Voted
PRL
2010
158views more  PRL 2010»
15 years 3 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