Projections onto the canonical simplex with additional linear inequalities

DOI10.1080/10556788.2020.1797023zbMath1501.90062arXiv1905.03488OpenAlexW3046448159MaRDI QIDQ5038426

Lukáš Adam, Václav Mácha

Publication date: 30 September 2022

Published in: Optimization Methods and Software (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1905.03488

zbMATH Keywords

projectionsimplexdistributionally robust optimizationlinear observed complexity

Mathematics Subject Classification ID

Numerical optimization and variational techniques (65K10) Quadratic programming (90C20) Numerical methods based on necessary conditions (49M05) Optimality conditions for free problems in two or more independent variables (49K10) Robustness in mathematical programming (90C17)

Uses Software

• SPGL1
• JuMP

Cites Work

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• Normally admissible stratifications and calculation of normal cones to a finite union of polyhedral sets
• Fast projection onto the simplex and the \(l_1\) ball
• A finite algorithm for finding the projection of a point onto the canonical simplex of \({\mathbb R}^ n\)
• Identifying effective scenarios in distributionally robust stochastic programs with total variation distance
• A linear-time median-finding algorithm for projecting a vector on the simplex of \({\mathbb{R}}^ n\)
• Distributionally robust SDDP
• Breakpoint searching algorithms for the continuous quadratic knapsack problem
• Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems
• Probing the Pareto Frontier for Basis Pursuit Solutions
• Validation of subgradient optimization
• A Simplex Method for Function Minimization
• JuMP: A Modeling Language for Mathematical Optimization
• A semismooth Newton method with analytical path-following for the $H^1$-projection onto the Gibbs simplex

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