We present a system-level approach for power optimization under a set of user specified costs and timing constraints of hard real-time designs. The approach optimizes all three d...
For two given point sets, we present a very simple (almost trivial) algorithm to translate one set so that the Hausdor distance between the two sets is not larger than a constant ...
In this paper we show that dimensionality reduction (i.e., Johnson-Lindenstrauss lemma) preserves not only the distances between static points, but also between moving points, and...
The paper presents a method for uncertainty propagation in Bayesian networks in symbolic, as opposed to numeric, form. The algebraic structure of probabilities is characterized. Th...
Abstract. Markov random fields are often used to model high dimensional distributions in a number of applied areas. A number of recent papers have studied the problem of reconstruc...