Achieving geometric convergence for distributed optimization with Barzilai-Borwein step sizes
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DOI: 10.1007/s11432-020-3256-x
Abstract: We consider a distributed multi-agent optimization problem over a time-invariant undirected graph, where each agent possesses a local objective function and all agents collaboratively minimize the average of all objective functions through local computations and… read more here.
Keywords: step sizes; step; geometric convergence; method ... See more keywords
Communication-Efficient Distributed Sparse Learning with Oracle Property and Geometric Convergence*
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DOI: 10.1080/01621459.2025.2479237
Abstract: Abstract This article introduces two highly efficient distributed non-convex sparse learning algorithms. Our approach accommodates non-convexity in both the loss function and penalty, acknowledging the potential non-uniqueness of local minimizers due to the inherent non-convexity.… read more here.
Keywords: non convexity; efficient distributed; geometric convergence; convergence ... See more keywords