In this paper, we propose a general cross-layer optimization framework in which we explicitly consider both the heterogeneous and dynamically changing characteristics of delay-sens...
We study the problem of learning a classification task in which only a dissimilarity function of the objects is accessible. That is, data are not represented by feature vectors bu...
Modeling long-term dependencies in time series has proved very difficult to achieve with traditional machine learning methods. This problem occurs when considering music data. In ...
— Consider a discrete-time networked control scheme, in which the controller has direct access to noisy measurements of the plant’s output, but the controller and the actuator ...
This paper proposes a methodology for designing a class of algorithms for computing functions in dynamic distributed systems in which communication channels and processes may ceas...