A tailored model of a system is the prerequisite for various analysis tasks, such as anomaly detection, fault identification, or quality assurance. This paper deals with the algo...
Oliver Niggemann, Benno Stein, Asmir Vodencarevic,...
Operational network data, management data such as customer care call logs and equipment system logs, is a very important source of information for network operators to detect prob...
Chi-Yao Hong, Matthew Caesar, Nick G. Duffield, Ji...
To avoid receiving incorrect arguments, a method specifies the expected type of each formal parameter. However, some parameter types are too general and have subtypes that the me...
In this work we propose a novel approach to anomaly detection in streaming communication data. We first build a stochastic model for the system based on temporal communication pa...
We introduce the Longterm Observation of Scenes (with Tracks) dataset. This dataset comprises videos taken from streaming outdoor webcams, capturing the same half hour, each day, ...
Austin Abrams, Jim Tucek, Joshua Little, Nathan Ja...
Sorting is among the most fundamental and well-studied problems within computer science and a core step of many algorithms. In this article, we consider the problem of constructing...
GPS-equipped taxis can be viewed as pervasive sensors and the large-scale digital traces produced allow us to reveal many hidden “facts” about the city dynamics and human beha...
Daqing Zhang, Nan Li, Zhi-Hua Zhou, Chao Chen, Lin...
This paper presents Yagada, an algorithm to search labelled graphs for anomalies using both structural data and numeric attributes. Yagada is explained using several security-rela...
Michael Davis, Weiru Liu, Paul Miller, George Redp...
Autonomy requires robustness. The use of unmanned (autonomous) vehicles is appealing for tasks which are dangerous or dull. However, increased reliance on autonomous robots increa...
Eliahu Khalastchi, Gal A. Kaminka, Meir Kalech, Ra...
This paper describes one of the first attempts to model the temporal structure of massive data streams in real-time using data stream clustering. Recently, many data stream clust...