This report presents a model-driven, stress test methodology aimed at increasing chances of discovering faults related to network traffic in Distributed Real-Time Systems (DRTS). T...
This paper considers the problem of an agent searching for a resource or a tangible good in a physical environment, where at each stage of its search it observes one source where ...
Yonatan Aumann, Noam Hazon, Sarit Kraus, David Sar...
The relationship between financial incentives and performance, long of interest to social scientists, has gained new relevance with the advent of web-based “crowd-sourcing” mo...
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
We describe a neurally-inspired, unsupervised learning algorithm that builds a non-linear generative model for pairs of face images from the same individual. Individuals are then ...