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    Accelerated Gossip via Stochastic Heavy Ball Method

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    Type
    Conference Paper
    Authors
    Loizou, Nicolas
    Richtarik, Peter cc
    KAUST Department
    Computer Science Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    KAUST, University of Edinburgh, MIPT, , , Saudi Arabia
    Date
    2019-03-01
    Online Publication Date
    2019-03-01
    Print Publication Date
    2018-10
    Permanent link to this record
    http://hdl.handle.net/10754/631783
    
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    Abstract
    In this paper we show how the stochastic heavy ball method (SHB)-a popular method for solving stochastic convex and non-convex optimization problems-operates as a randomized gossip algorithm. In particular, we focus on two special cases of SHB: the Randomized Kaczmarz method with momentum and its block variant. Building upon a recent framework for the design and analysis of randomized gossip algorithms [20] we interpret the distributed nature of the proposed methods. We present novel protocols for solving the average consensus problem where in each step all nodes of the network update their values but only a subset of them exchange their private values. Numerical experiments on popular wireless sensor networks showing the benefits of our protocols are also presented.
    Citation
    Loizou N, Richtarik P (2018) Accelerated Gossip via Stochastic Heavy Ball Method. 2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton). Available: http://dx.doi.org/10.1109/ALLERTON.2018.8636082.
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton)
    Conference/Event name
    56th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2018
    DOI
    10.1109/ALLERTON.2018.8636082
    Additional Links
    https://ieeexplore.ieee.org/document/8636082
    ae974a485f413a2113503eed53cd6c53
    10.1109/ALLERTON.2018.8636082
    Scopus Count
    Collections
    Conference Papers; Computer Science Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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