Laplacian Smoothing Stochastic ADMMs With Differential Privacy Guarantees
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DOI: 10.1109/tifs.2022.3170271
Abstract: Many machine learning tasks such as structured sparse coding and multi-task learning can be converted into an equality constrained optimization problem. The stochastic alternating direction method of multipliers (SADMM) is a popular algorithm to solve… read more here.
Keywords: smoothing stochastic; stochastic admm; privacy; equality constrained ... See more keywords