Abstract— Meta-Learning has been used to predict the performance of learning algorithms based on descriptive features of the learning problems. Each training example in this cont...
The problem of detecting "atypical objects" or "outliers" is one of the classical topics in (robust) statistics. Recently, it has been proposed to address this...
One of the biggest challenges facing digital investigators is the sheer volume of data that must be searched in locating the digital evidence. How to efficiently locate the eviden...
Sensor networks play a central role in applications that monitor variables in geographic areas such as the traffic volume on roads or the temperature in the environment. A key fea...
In this paper we show that Ullman and Basri’s linear combination (LC) representation, which was originally proposed for alignment-based object recognition, can be used for outli...