SIAM Optimization 2017 での SDP 関係の発表を一覧にしてみた

SIAM Optimization 2017 での SDP 関係がどんなものがあるのかを調べてみたので、一覧を掲載しておく。
基本的にはタイトルだけだけど、タイトルかアブストラクトに semidefinite と入っているものを網羅的に並べてある。ただ、人力でやっているので、１つや２つは見落としがあるかもしれない。
つまり、
https://www.siam.org/meetings/op17/op17_abstracts.pdf
で semidefinite と検索したということ。

タイトルの数としては６０個ぐらいで、多いのは SDP 緩和関係のお話。あと、最近の話題としては、量子計算と絡んでいるものが増えている傾向がある。


[1]  A Primal Majorized Newton-CG Augmented Lagrangian Method for Large-Scale Linearly Constrained Convex Programming
[2]  A Semidefinite Programming Approach for Energy Network Planning
[3]  Simultaneous Truss Topology - and Static Output Feedback Controller Design via Nonlinear Semidefinite Programming
[4] Copositive Optimization on Infinite Graphs
[5] The Cone of Positive Type Measures on a Compact Group
[6] Convergence Rates of the Moment-Sum-of-Squares Hierarchy for Volume Approximation of Semialgebraic Sets
[7] A Two-Phase Algorithm for Large-Scale Qplogdet Optimization Problem
[8] Convex Relaxations with Second Order Cone Constraints for Nonconvex Quadratically Constrained Quadratic Programming
[9] Completely Positive and Positive Semidefinite Tensor Relaxations for Polynomial Optimization
[10] Analysis of Newton’s Method via Semidefinite Programming Performance Estimation Problems
[11] Perturbation Analysis of Singular Semidefinite Programming via the Facial Reduction
[12] Polynomial Norms
[13] Inner and Outer Approximations of the Semidefinite Cone Using SD Bases and their Applications to Some NP-Hard Problems
[14] Tensor Eigenvalue Complementarity Problems
[15]  More NP-Hard Tensor Problems
[16] Real Eigenvalues of Nonsymmetric Tensors
[17] Pajarito: An Open-Source Mixed-Integer Conic Solver
[18] SCIP-SDP: A Framework for Solving Mixed-Integer Semidefinite Programs
[19] Sums of Squares and Matrix Completion
[20] Polynomial Optimization with Sum-of-Squares Interpolants
[21] Polynomials as Sums of Few Squares
[22] Relaxations and Convex Hull Results for the Intersection of Elementary Nonconvex Quadratics and General Regular Cones
[23] Semidefinite Approximations of Matrix Logarithm
[24] A Positivstellensatz for Sums of Nonnegative Circuit Polynomials
[25] Exploring the Second Order Sparsity in Large Scale Optimization
[26] Low-Rank Matrix Completion (LRMC) Using Nuclear Norm (NN) with Facial Reduction (FR)
[27] Lieb’s Concavity Theorem, Matrix Geometric Means, and Semidefinite Optimization
[28] Solving Generic Nonarchimedean Semidefinite Programs Using Stochastic Game Algorithms
[29] A Generalized Alternating Direction Method of Multipliers with Semi-Proximal Terms for Convex Composite Conic Programming
[30] Nonconvex Low-Rank Estimation: Robustness and Linear Convergence
[31] Dropping Convexity for Faster Semidefinite Optimization
[32] Automating the Analysis and Design of Large-Scale Optimization Algorithms
[33] A Lifted-Polyhedral-Programming Approach for Optimal Contribution Problems
[34] Conic Infimum and Supremum and Some Applications
[35] On Positive Duality Gaps in Semidefinite Programming
[36] Dimension Reduction for SDP
[37] Semidefinite Programming Relaxations and Multigrid Methods in Optimal Control
[38] A Copositive Approach for Two-Stage Adjustable Robust Optimization with Uncertain Right-Hand Sides
[39] Low-Complexity Relaxations and Convex Hulls of Disjunctions on the Positive Semidefinite Cone and Other Regular Cones
[40] Conic Programming Reformulations of Two-Stage Distributionally Robust Linear Programs over Wasserstein Balls
[41] Appointment Scheduling under Schedule-Dependent Patient No-Show Behavior
[42] A Data-Driven Distributionally Robust Bound on the Expected Optimal Value of Uncertain Mixed 0-1 Linear Programming
[43] On the Construction of Exact Augmented Lagrangian Functions for Nonlinear Semidefinite  Optimization
[44] An Extension of Chubanov’s Algorithm to Symmetric Cones
[45] Low-Order Complexity Results for SOS/SDP Methods in Real Algebra
[46] Convex Relaxation Without Lifting: Solving Large Semidefinite Programs without all the Pain
[47] Electronic Structure Calculation using Semidefinite Programs
[48] Estimation Performance and Convergence Rate of the Generalized Power Method for Phase Synchronization
[49] Computational Study of Some Valid Inequalities for k-Way Graph Partitioning
[50] Graph Bisection Revisited
[51] From Clifford Algebras and Rigidity Theory to Large Completely Positive Semidefinite Rank
[52] Quantum Correlations: Conic Formulations, Dimension Bounds and Matrix Factorizations
[53] Rank Minimization using a Complementarity Approach
[54] Quantum Bilinear Optimization
[55] Quantum Channels, Spectrahedra and a Tracial Hahn-Banach Theorem
[56] Using Noncommutative Polynomial Optimization for Matrix Factorization Ranks
[57] Optimization of Spatiotemporal Fractionation in Photon Radiotherapy with Optimality Bounds
[58] Finding Planted Graphs with Few Eigenvalues using the Schur-Horn Relaxation
[59] Semidefinite Programs with a Dash of Smoothness: Why and When the Low-Rank Approach Works
[60]  Gradient Descent for Rectangular Matrix Completion
[61] Analyzing Quantum Cryptographic Protocols using Semidefinite Programming
[62] Quantum Speed-Ups for Semidefinite Programming