一応、著者の一人なので Handbook on Semidefinite, Conic and Polynomial Optimization も一冊もらえるらしいが、まだ到着していない。
２４章
◯Latest Developments in the SDPA Family for Solving Large-Scale SDPs
Makoto Yamashita, Katsuki Fujisawa,Mituhiro Fukuda, Kazuhiro Kobayashi, Kazuhide Nakata, and Maho Nakata
Handbook on Semidefinite, Conic and Polynomial Optimization (International Series in Operations Research & Management Science)
書籍はタイムラグが多いので仕方が無いのだが、SDPARA の結果も古くなっていて、高精度の計算の話が少ないのがやや残念なところ。
以下は本の目次だが Application に関する内容も多く、何か面白そうな SDP の応用を発掘できれば幸い。
Table of contents
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.
Compositive 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 SDP's.
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.
２４章
◯Latest Developments in the SDPA Family for Solving Large-Scale SDPs
Makoto Yamashita, Katsuki Fujisawa,Mituhiro Fukuda, Kazuhiro Kobayashi, Kazuhide Nakata, and Maho Nakata
Handbook on Semidefinite, Conic and Polynomial Optimization (International Series in Operations Research & Management Science)
書籍はタイムラグが多いので仕方が無いのだが、SDPARA の結果も古くなっていて、高精度の計算の話が少ないのがやや残念なところ。
以下は本の目次だが Application に関する内容も多く、何か面白そうな SDP の応用を発掘できれば幸い。
Table of contents
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.
Compositive 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 SDP's.
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.
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