Jan 14, 2017 · We present a new class of decentralized first-order methods for nonsmooth and stochastic optimization problems defined over multiagent networks.
Dec 7, 2018 · We present a new class of decentralized first-order methods for nonsmooth and stochastic optimization problems defined over multiagent networks.
Abstract We present a new class of decentralized first-order methods for nonsmooth and stochastic optimization problems defined over multiagent networks.
Abstract We present a new class of decentralized first-order methods for nonsmooth and stochastic optimization problems defined over multiagent networks.
We present a new class of decentralized first-order methods for nonsmooth and stochastic optimization problems defined over multiagent networks.
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PORTER utilizes stochastic gradient tracking, communication compression together with error feedback as BEER does, and further leverages Gaussian perturbation ...
Dec 7, 2018 · Abstract. We present a new class of decentralized first-order methods for nonsmooth and stochastic optimization problems defined over ...
Jun 19, 2022 · Bibliographic details on Communication-Efficient Algorithms for Decentralized and Stochastic Optimization.
Decentralized learning algorithms empower interconnected devices to share data and computational resources to collaboratively train a machine learning model ...
Apr 5, 2021 · Abstract—Recently, the technique of local updates is a powerful tool in centralized settings to improve communication efficiency.