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SIGKDD
2008
113views more  SIGKDD 2008»
15 years 6 months ago
On exploiting the power of time in data mining
We introduce the new paradigm of Change Mining as data mining over a volatile, evolving world with the objective of understanding change. While there is much work on incremental m...
Mirko Böttcher, Frank Höppner, Myra Spil...
MICRO
2003
IEEE
155views Hardware» more  MICRO 2003»
15 years 11 months ago
Comparing Program Phase Detection Techniques
Detecting program phase changes accurately is an important aspect of dynamically adaptable systems. Three dynamic program phase detection techniques are compared – using instruc...
Ashutosh S. Dhodapkar, James E. Smith
RAID
2004
Springer
15 years 11 months ago
Seurat: A Pointillist Approach to Anomaly Detection
Abstract. This paper proposes a new approach to detecting aggregated anomalous events by correlating host file system changes across space and time. Our approach is based on a key...
Yinglian Xie, Hyang-Ah Kim, David R. O'Hallaron, M...
392
Voted
CVPR
2012
IEEE
13 years 11 months ago
Foreground Detection Using Spatiotemporal Projection Kernels
Foreground detection is at the core of many video processing tasks. In this paper, we propose a novel video foreground detection method that exploits the statistics of 3D space-tim...
Y. Moshe, H. Hel-Or, and Y. Hel-Or
ICDE
2012
IEEE
223views Database» more  ICDE 2012»
13 years 8 months ago
Incremental Detection of Inconsistencies in Distributed Data
—This paper investigates the problem of incremental detection of errors in distributed data. Given a distributed database D, a set Σ of conditional functional dependencies (CFDs...
Wenfei Fan, Jianzhong Li, Nan Tang, Wenyuan Yu