Non-IID federated learning

Longbing Cao

doi:10.1109/MIS.2022.3167955

Non-IID federated learning

Research output: Contribution to journal › Other journal contribution

Abstract

This issue features the technical theme on “Non-IID Federated Learning,” an important topic in addressing non-IIDness (independent and identically distributed) and other progress in distributed and federated learning.

Original language	English
Pages (from-to)	14-15
Number of pages	2
Journal	IEEE Intelligent Systems
Volume	37
Issue number	2
DOIs	https://doi.org/10.1109/MIS.2022.3167955
Publication status	Published - 2022
Externally published	Yes

Access to Document

10.1109/MIS.2022.3167955

Cite this

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title = "Non-IID federated learning",

abstract = "This issue features the technical theme on “Non-IID Federated Learning,” an important topic in addressing non-IIDness (independent and identically distributed) and other progress in distributed and federated learning.",

author = "Longbing Cao",

year = "2022",

doi = "10.1109/MIS.2022.3167955",

language = "English",

volume = "37",

pages = "14--15",

journal = "IEEE Intelligent Systems",

issn = "1541-1672",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

number = "2",

}

TY - JOUR

T1 - Non-IID federated learning

AU - Cao, Longbing

PY - 2022

Y1 - 2022

N2 - This issue features the technical theme on “Non-IID Federated Learning,” an important topic in addressing non-IIDness (independent and identically distributed) and other progress in distributed and federated learning.

AB - This issue features the technical theme on “Non-IID Federated Learning,” an important topic in addressing non-IIDness (independent and identically distributed) and other progress in distributed and federated learning.

U2 - 10.1109/MIS.2022.3167955

DO - 10.1109/MIS.2022.3167955

M3 - Other journal contribution

SN - 1541-1672

VL - 37

SP - 14

EP - 15

JO - IEEE Intelligent Systems

JF - IEEE Intelligent Systems

IS - 2

ER -