We present a deterministic model for on-line social networks based on transitivity and local knowledge in social interactions. In the Iterated Local Transitivity (ILT) model, at ea...
Anthony Bonato, Noor Hadi, Paul Horn, Pawel Pralat...
— Reinforcement learning (RL) is a learning control paradigm that provides well-understood algorithms with good convergence and consistency properties. Unfortunately, these algor...
Lucian Busoniu, Damien Ernst, Bart De Schutter, Ro...
Consider a heterogeneous cluster system, consisting of processors with varying processing capabilities and network links with varying bandwidths. Given a DAG application to be sch...
the emergence of Internet and new kind of architecture, likepeer-to-peer (P2P) networks, provides great hope for distributed computation. However, the combination of the world of ...
— We consider a network of distributed sensors, where each sensor takes a linear measurement of some unknown parameters, corrupted by independent Gaussian noises. We propose a si...