Incremental gradient method for Karcher mean on symmetric cones

DOI10.1007/s10957-016-1000-4zbMath1432.65056OpenAlexW2509676920MaRDI QIDQ511964

Sangho Kum, Sangwoon Yun

Publication date: 23 February 2017

Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10957-016-1000-4

zbMATH Keywords

symmetric coneKarcher meanincremental gradient method

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Convex programming (90C25) Positive matrices and their generalizations; cones of matrices (15B48) Numerical linear algebra (65F99)

Related Items (2)

First Order Methods for Optimization on Riemannian Manifolds ⋮ Computing Riemannian center of mass on Hadamard manifolds

Uses Software

• Matrix Means Toolbox

Cites Work

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• No dice theorem on symmetric cones
• Convexity and differentiability properties of spectral functions and spectral mappings on Euclidean Jordan algebras
• Computing the Karcher mean of symmetric positive definite matrices
• Incrementally updated gradient methods for constrained and regularized optimization
• Penalized complementarity functions on symmetric cones
• A survey and comparison of contemporary algorithms for computing the matrix geometric mean
• On the Convergence of Gradient Descent for Finding the Riemannian Center of Mass
• Computing Medians and Means in Hadamard Spaces
• Löwner's Operator and Spectral Functions in Euclidean Jordan Algebras
• Monotone vector fields and the proximal point algorithm on Hadamard manifolds
• Riemannian center of mass and mollifier smoothing
• Domains of positivity

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