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Distributed learning is envisioned as the bedrock of next-generation intelligent networks, where intelligent agents, such as mobile devices, robots, and sensors, exchange information with each other or a parameter server to train machine learning models collaboratively without uploading raw data to a central entity for ...
Feb 6, 2023
Feb 8, 2023 · In this paper, we present a comprehensive survey of prevailing methodologies for communication-efficient distributed learning, including reduc-.
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Apr 1, 2023 · Distributed learning is envisioned as the bedrock of next-generation intelligent networks, where intelligent agents, such as mobile devices, ...
In this paper, we present a comprehensive survey of prevailing methodologies for communication-efficient distributed learning, including reduc- tion of the ...
Oct 8, 2023 · Here, we develop a communication-efficient distributed algorithm for computing the leading invariant subspace of a data matrix. Our algorithm ...
Mar 10, 2020 · We first propose a taxonomy of data-parallel distributed training algorithms that incorporates four primary dimensions: communication ...
In this tutorial, we provide a systematic introduction of communication efficient distributed learning and review frontier papers in this active research topic.
Distributed machine learning is envisioned as the bedrock of future intelligent networks and Internet-of-Things (IoT), where intelligent agents exchange ...
Apr 1, 2023 · Distributed machine learning is envisioned as the bedrock of future intelligent networks, where agents exchange information with each other ...
As machine learning moves away from data-center architectures to learning with edge devices (like smartphones, IoT sensors etc.) ...