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Totally Convex Functions for Fixed Points Computation and Infinite Dimensional Optimization

The main purpose of this book is to present, in a unified approach, several algorithms for fixed point computation, convex feasibility and;

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Convex and Set-Valued Analysis

of convex cones in finite- and infinite-dimensional spaces are discussed. The second part covers some important parts of set-valued analysis. There;

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Constructive Real Analysis

defined on subsets of finite and infinite dimensional spaces. Rather than citing practical algorithms for solving problems, this treatment;

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Statistical Inference via Convex Optimization

optimization theory can be used to devise and analyze near-optimal statistical inferences. Statistical Inference via Convex Optimization is an;

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Even Convexity and Optimization

convex sets. The book introduces their application to convex optimization. Particular attention is paid to evenly convex polyhedra and finite;

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Even Convexity and Optimization

convex sets. The book introduces their application to convex optimization. Particular attention is paid to evenly convex polyhedra and finite;

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Convexity And Optimization In Rn

Convex functions Optimization problems Convex programming and duality The simplex method A detailed bibliography is included for further study;

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Relative Optimization of Continuous-Time and Continuous-State Stochastic Systems

classification for time nonhomogeneous continuous processes and multi-class optimization; and development of the multi-dimensional Tanaka formula for;

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Relative Optimization of Continuous-Time and Continuous-State Stochastic Systems

classification for time nonhomogeneous continuous processes and multi-class optimization; and development of the multi-dimensional Tanaka formula for;

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Cambridge Tracts in Mathematics

a comprehensive insight into convex sets and functions including the infinite-dimensional case and emphasizing the analytic point of view;

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Classical And Modern Optimization

The quest for the optimal is ubiquitous in nature and human behavior. The field of mathematical optimization has a long history and remains;

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Classical And Modern Optimization

The quest for the optimal is ubiquitous in nature and human behavior. The field of mathematical optimization has a long history and remains;

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Optimality Conditions in Convex Optimization

finite dimensions to allow for much deeper results and a better understanding of the structures involved in a convex optimization problem. They;

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Convex Analysis and Variational Problems

programming in the context of convex analysis, including duality, minmax and Lagrangians, and convexification of nonconvex optimization problems;

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Convex Optimization

This book provides easy access to the basic principles and methods for solving constrained and unconstrained convex optimization problems;

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Pseudolinear Functions and Optimization

Pseudolinear Functions and Optimization is the first book to focus exclusively on pseudolinear functions, a class of generalized convex;

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Pseudolinear Functions and Optimization

Pseudolinear Functions and Optimization is the first book to focus exclusively on pseudolinear functions, a class of generalized convex;

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Topological Vector Spaces and Their Applications

topological vector spaces. Overall, this book develops differential and integral calculus on infinite-dimensional locally convex spaces by using;

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Fixed Point Theory, Variational Analysis, and Optimization

Fixed Point Theory, Variational Analysis, and Optimization not only covers three vital branches of nonlinear analysis-fixed point theory;

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Nonlinear Analysis, Differential Equations, and Applications

numerical schemes for differential equations, the Erdos-Renyi network model, strongly m-convex functions, higher order strongly generalized convex;

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Algorithms for Solving Common Fixed Point Problems

This book details approximate solutions to common fixed point problems and convex feasibility problems in the presence of perturbations;

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Bifurcation and Stability in Nonlinear Discrete Systems

the local monotonic and oscillatory stability and bifurcation of period-1 fixed-points on a specific eigenvector direction, and discusses the;

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Geometry of Convex Sets

concepts of vector addition and scalar multiplication and then defines the notion of convexity for subsets of n-dimensional space. Many properties;

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Symposium on Infinite Dimensional Topology. (AM-69), Volume 69

linear spaces, fixed point theory in infinite dimensional spaces, infinite dimensional differential topology, and infinite dimensional pointset;

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Nonlinear Analysis and Global Optimization

, optimization models for networks of organ transplants, network curvature measures, error analysis through energy minimization and stability problems;

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Optimization

sistent approximations and algorithm implementation techniques. Traditionally, necessary optimality conditions for optimization problems are;

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Convex Optimization & Euclidean Distance Geometry

Optimization is the science of making a best choice in the face of conflicting requirements. Any convex optimization problem has geometric;

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