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...
ut spatial environments, be it real or abstract, human or machine. Research issues range from human spatial cognition to mobile robot navigation. Numerous results have been obtaine...
Christian Freksa, Holger Schultheis, Kerstin Schil...
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...