swMATH ID: 38277
Software Authors: Artiom Kovnatsky, Klaus Glashoff, Michael M. Bronstein
Description: MADMM: a generic algorithm for non-smooth optimization on manifolds. Numerous problems in machine learning are formulated as optimization with manifold constraints. In this paper, we propose the Manifold alternating directions method of multipliers (MADMM), an extension of the classical ADMM scheme for manifold-constrained non-smooth optimization problems and show its application to several challenging problems in dimensionality reduction, data analysis, and manifold learning.
Homepage: https://arxiv.org/abs/1505.07676
Related Software: Manopt; SDPLR; Matrix Means Toolbox; FPC_AS; FMS; GradSamp; AdaGrad; BiqMac; Biq Mac; PDCO; CVX; Spectra; Europarl; PMA; Steerable pyramid; Manopt.jl; Camino; RecPF; UCI-ml; ROPTLIB
Cited in: 16 Publications

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