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...
Detecting program phase changes accurately is an important aspect of dynamically adaptable systems. Three dynamic program phase detection techniques are compared – using instruc...
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...
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...
—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...