- Print ISBN 9780444505958
- Electronic ISBN 9780080508764
Inherently parallel algorithms, that is, computational methods which are, by their mathematical nature, parallel, have been studied in various contexts for more than fifty years. However, it was only during the last decade that they have mostly proved their practical usefulness because new generations of computers made their implementation possible in order to solve complex feasibility and optimization problems involving huge amounts of data via parallel processing. These led to an accumulation of computational experience and theoretical information and opened new and challenging questions concerning the behavior of inherently parallel algorithms for feasibility and optimization, their convergence in new environments and in circumstances in which they were not considered before their stability and reliability. Several research groups all over the world focused on these questions and it was the general feeling among scientists involved in this effort that the time has come to survey the latest progress and convey a perspective for further development and concerted scientific investigations. Thus, the editors of this volume, with the support of the Israeli Academy for Sciences and Humanities, took the initiative of organizing a Workshop intended to bring together the leading scientists in the field. The current volume is the Proceedings of the Workshop representing the discussions, debates and communications that took place. Having all that information collected in a single book will provide mathematicians and eng
Projection algorithms: Results and open problems (H.H. Bauschke).
Joint and separate convexity of the bregman distance (H.H. Bauschke, J.M. Borwein).
A parallel algorithm for non-cooperative resource allocation games (L.M. Bregman, I.N. Fokin).
Asymptotic behavior of quasi-nonexpansive mappings (D. Butnariu, S. Reich, A.J. Zaslavski).
The outer bregman projection method for stochastic feasibility problems in banach spaces (D. Butnariu, E. Resmerita).
Bregman-legendre multidistance projection algorithms for convex feasibility and optimization (C. Byrne).
Averaging strings of sequential iterations for convex feasibility problems (Y. Censor, T. Elfving, G.T. Herman).
Quasi-fejerian analysis of some optimization algorithms (P.L. Combettes).
On the theory and practice of row relaxation methods (A. Dax).
From parallel to sequential projection methods and vice versa in convex feasibility: Results and conjectures (A.R. De Pierro).
Accelerating the convergence of the meth