The stochastic approximation method is behind the solution to many important, actively-studied problems in machine learning. Despite its farreaching application, there is almost n...
This paper reports on and discusses three notions of approximation for Labelled Markov Processes that have been developed last year. The three schemes are improvements over former...
Millions of research funding has been put down to develop - what I call - old forms - of reasoning that are characterized by strong focus on theoretical properties and strict adher...
In this paper, we address the matrix completion problem and propose a novel algorithm based on a smoothed rank function (SRF) approximation. Among available algorithms like FPCA a...
—This paper studies the performance of ad hoc networks with local FDMA scheduling using stochastic point processes. In such networks, the Poisson assumption is not justified due...