In this work, we propose a new, fast and scalable method for anomaly detection in large time-evolving graphs. It may be a static graph with dynamic node attributes (e.g. time-series), or a graph evolving in time, such as a temporal network. We define an an ...
Information about world events is disseminated through a wide variety of news channels, each with specific considerations in the choice of their reporting. Although the multiplicity of these outlets should ensure a variety of viewpoints, recent reports sug ...
Implantable electronic medical device (IEMD) is an emerging technology that plays an important role in the treatment of several neurological disorders such as epilepsy, especially in the cases of drug-resistant epilepsy. Recent developments and studies sho ...
The application of orthogonal sampling for parallel neural recording is presented in this paper. Orthogonal sampling enables reducing the number of the I Cs in conventional recording systems into one single unit. Consequently, the ADC bandwidth and dynamic ...
The increasing amount of data collected in online learning environments provides unique opportunities to better understand the learning processes in different educational settings. Learning analytics research aims at understanding and optimizing learning a ...
Subgraph counting is a fundamental primitive in graph processing, with applications in social network analysis (e.g., estimating the clustering coefficient of a graph), database processing and other areas. The space complexity of subgraph counting has been ...
The connectivity of a neuronal network has a major effect on its functionality and role. It is generally believed that the complex network structure of the brain provides a physiological basis for information processing. Therefore, identifying the network’ ...
