Handbook on Semidefinite, Conic and Polynomial Optimization

Introduction to Semidefinite, Conic and Polynomial Optimization -- The Approach of Moments for Polynomial Equations -- Algebraic Degree in Semidefinite and Polynomial Optimization -- Semidefinite Representation of Convex Sets and Convex Hulls -- Convex Hulls of Algebraic Sets -- Convex Relations and Integrality Gaps -- Relaxations of Combinatorial Problems via Association Schemes -- Copositive Programming -- Invariant Semidefinite Programs -- A "Joint+Marginal" Approach in Optimization -- An Introduction to Formally Real Jordan Algebras and Their Applications in Optimization -- Complementarity Problems Over Symmetric Conics: A Survey of Recent Developments in Several Aspects -- Convexity and Semidefinite Programming in Dimension-Free Matrix Unknowns -- Positivity and Optimization: Beyond Polynomials -- Self-Regular Interior-Point Methods for Semidefinite Optimization -- Elementary Optimality Conditions for Nonlinear SDPs -- Recent Progress in Interior-Point Methods: Cutting Plane Algorithms and Warm Starts -- Exploiting Sparsity in SDP Relaxation of Polynomial Optimization Problems -- Block Coordinate Descent Methods for Semidefinite Programming -- Projection Methods in Conic Optimization -- SDP Relaxations for Non-Commutative Polynomial Optimization -- Semidefinite Programming and Constraint Programming -- The State-of-the-Art in Conic Optimization Software -- Latest Developments in SDPA Family for Solving Large-Scale SDPs -- On the Implementation and Usage of SDPT3: A MATLAB Software Package for Semidefinite-Quadratic-Linear Programming, Version 4.0 -- PENNON: Software for Linear and Nonlinear Matrix Inequalities -- SDP Relaxations for Some Combinatorial Optimization Problems -- Computational Approaches to Max-Cut -- Global Approaches for Facility Layout and VLSI Floorplanning -- Euclidean Distance Matrices and Applications -- Sparse PCA: Convex Relaxations, Algorithms and Applications