Optimization and Its Applications in Control and Data Sciences: In Honor of Boris T. Polyak's 80th Birthday

Book Overview

Introduction: Big, Small, and Optimal Steps of Boris Polyak (Boris Goldengorin).- A Convex Optimization Approach to Modeling of Stationary Periodic Time Series (Anders Lindquist and Giorgio Picci).- New two-phase proximal method of solving the solving the problem of equilibrium programming (Sergey I. Lyashko and Vladimir V. Semenov).- Minimax Control of Positive Switching Systems with Markovian Jumps (Patrizio Colaneri, Jos? Geromel, Paolo Bolzern, Grace Deaecto).- A modified Polak-Ribi?re-Polyak conjugate gradient algorithm with sufficient descent and conjugacy properties for unconstrained optimization (Neculai Andrei).- Subgradient method with the transformation of space and Polyak's step (Petro Stetsyuk).- Invariance Conditions for Nonlinear Dynamical Systems (Y. Song, and T. Terlaky).- Nonparametric ellipsoidal approximation of compact sets of random points (S. I., Lyashko, V.V. Semenov D.A. Klyushin, M.V. Prysyazhna, M.P. Shlykov).- Algorithmic Principle of the Least Excessive Revenue for finding market equilibria (Yurii Nesterov, Vladimir Shikhman).- Matrix-Free Convex Optimization Modeling (Stephen Boyd and Steven Diamond).- Stochastic Optimization and Statistical Learning in Reproducing Kernel Hilbert Spaces the Stochastic Quasi-Gradient Methods (Vladimir I. Norkin).

• Format: Paperback
• Language: English
• ISBN: 3319824902
• ISBN13: 9783319824901
• Release Date: June 2018
• Publisher: Springer
• Length: 507 Pages
• Weight: 1.61 lbs.
• Dimensions: 1.1" x 6.1" x 9.2"