Here we advocate an approach to learning hardware based on induction of finite state machines from temporal logic constraints. The method involves training on examples, constraint...
Marek A. Perkowski, Alan Mishchenko, Anatoli N. Ch...
This paper deals with finding outliers (exceptions) in large, multidimensional datasets. The identification of outliers can lead to the discovery of truly unexpected knowledge in ...
Many applications require the management of spatial data. Clustering large spatial databases is an important problem which tries to find the densely populated regions in the featu...
The knowledge discovery process encounters the difficulties to analyze large amount of data. Indeed, some theoretical problems related to high dimensional spaces then appear and de...
Most data mining algorithms assume static behavior of the incoming data. In the real world, the situation is different and most continuously collected data streams are generated by...
Lior Cohen, Gil Avrahami, Mark Last, Abraham Kande...