A framework for the regularized estimation of nonuniform dimensionality and density in high dimensional data is introduced in this work. This leads to learning stratifications, th...
Traditional databases store sets of relatively static records with no pre-defined notion of time, unless timestamp attributes are explicitly added. While this model adequately rep...
This paper is focused on adapting symmetry reduction, a technique that is highly successful in traditional model checking, to stochastic hybrid systems. To that end, we first sho...
—Sensory inputs such as visual images or audio spectrograms can act as symbols in a new cognitive model. The stability of direct image association operators allows the discrete b...
This paper presents a general framework for analyzing and designing embedded systems with energy and timing requirements. A set of realistic assumptions is considered in the model...