We consider a multi-agent system where each agent is equipped with a Bayesian network, and present an open framework for the agents to agree on a possible consensus network. The f...
We present an achievable rate for general Gaussian relay networks. We show that the achievable rate is within a constant number of bits from the information-theoretic cut-set uppe...
Amir Salman Avestimehr, Suhas N. Diggavi, David N....
A common assumption in supervised learning is that the training and test input points follow the same probability distribution. However, this assumption is not fulfilled, e.g., in...
—We use recent network calculus results to study some properties of lossless multiplexing as it may be used in guaranteed service networks. We call network calculus a set of resu...
The paper describes a framework in the form of an optimization of a performance index subject to the constraints of a dynamic network, represented in the state space. The performa...