Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...
Networks-on-Chip (NoCs) have recently emerged as a scalable alternative to classical bus and point-to-point architectures. To date, performance evaluation of NoC designs is largel...
A generic theoretical framework for managing critical events in ubiquitous computing systems is presented. The main idea is to automatically respond to occurrences of critical eve...
Tridib Mukherjee, Krishna M. Venkatasubramanian, S...
Abstract. Inverse reinforcement learning addresses the general problem of recovering a reward function from samples of a policy provided by an expert/demonstrator. In this paper, w...
Abstract—The adoption of new hardware and software architectures will make future generations of pervasive devices more flexible and extensible. Networks of computational nodes ...
Alberto Ferrante, Roberto Pompei, Anastasia Stulov...