DisMUSE: an efficient distributed singular-spectrum-based optimization approach with theoretical convergence guarantee
Read the original at arxiv.org→arXiv:2611.10212v1 Announce Type: new Abstract: In recent years, singular-spectrum-based optimizers have attracted increasing attention due to their ability to preserve the matrix structure of neural network...
Original headline: "DisMUSE: An Efficient Distributed Singular-Spectrum-Based Optimization Approach with Theoretical Convergence Guarantee"
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- Nov 10, 05:00 UTC arXiv cs.LG lead source DisMUSE: An Efficient Distributed Singular-Spectrum-Based Optimization Approach with Theoretical Convergence Guarantee