Buch, Englisch, Band 2227, 412 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 645 g
Reihe: Lecture Notes in Mathematics
Buch, Englisch, Band 2227, 412 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 645 g
Reihe: Lecture Notes in Mathematics
ISBN: 978-3-319-97477-4
Verlag: Springer International Publishing
Large-Scale and Distributed Optimization is a unique combination of contributions from leading experts in the field, who were speakers at the LCCC Focus Period on Large-Scale and Distributed Optimization, held in Lund, 14th–16th June 2017. A source of information and innovative ideas for current and future research, this book will appeal to researchers, academics, and students who are interested in large-scale optimization.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Optimierung
- Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Regelungstechnik
Weitere Infos & Material
- Large-Scale and Distributed Optimization: An Introduction. - Exploiting Chordality in Optimization Algorithms for Model Predictive Control. - Decomposition Methods for Large-Scale Semidefinite Programs with Chordal Aggregate Sparsity and Partial Orthogonality. - Smoothing Alternating Direction Methods for Fully Nonsmooth Constrained Convex Optimization. - Primal-Dual Proximal Algorithms for Structured Convex Optimization: A Unifying Framework. - Block-Coordinate Primal-Dual Method for Nonsmooth Minimization over Linear Constraints. - Stochastic Forward Douglas-Rachford Splitting Method for Monotone Inclusions. - Mirror Descent and Convex Optimization Problems with Non-smooth Inequality Constraints. - Frank-Wolfe Style Algorithms for Large Scale Optimization. - Decentralized Consensus Optimization and Resource Allocation. - Communication-Efficient Distributed Optimization of Self-concordantEmpirical Loss. - Numerical Construction of Nonsmooth Control Lyapunov Functions. - Convergence of an Inexact Majorization-Minimization Method for Solving a Class of Composite Optimization Problems.