Abstract. We advocate to analyze the average complexity of learning problems. An appropriate framework for this purpose is introduced. Based on it we consider the problem of learni...
An analysis is presented of the primary factors influencing the performance of a parallel implementation of the UCLA atmospheric general circulation model (AGCM) on distributedme...
In this paper we present a methodology and techniques for generating cycle-accurate macro-models for RTlevel power analysis. The proposed macro-model predicts not only...
—In this paper, we study node connectivity in multi-hop wireless networks. Nodal degree of connectivity as one of the fundamental graph properties is the basis for the study of n...
Abstract. In this paper, we describe an unsupervised learning framework to segment a scene into semantic regions and to build semantic scene models from longterm observations of mo...