ADMM-softmax: an ADMM approach for multinomial logistic regression

DOI10.1553/etna_vol52s214OpenAlexW3016792721MaRDI QIDQ1988494

Lars Ruthotto, Sanna Tyrväinen, Samy Wu Fung, Eldad Haber

Publication date: 23 April 2020

Published in: ETNA. Electronic Transactions on Numerical Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1901.09450

zbMATH Keywords

classificationnonlinear optimizationmachine learningalternating direction method of multipliersmultinomial regression

Mathematics Subject Classification ID

Convex programming (90C25) Decomposition methods (49M27) Numerical solution to inverse problems in abstract spaces (65J22)

Related Items (4)

Feasibility-based fixed point networks ⋮ Wasserstein-Based Projections with Applications to Inverse Problems ⋮ PNKH-B: A Projected Newton--Krylov Method for Large-Scale Bound-Constrained Optimization ⋮ ADMM-Softmax

Uses Software

• Regularization tools
• RestoreTools
• PDCO
• UTV
• MNIST
• CIFAR
• ImageNet
• IR Tools
• Meganet
• AlexNet

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