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Title:
OPTIMAL SPLIT FEDERATED LEARNING IN WIRELESS NETWORK
Document Type and Number:
WIPO Patent Application WO/2023/211081
Kind Code:
A1
Abstract:
Embodiment herein provide method and a system (100) for optimal Split Federated Learning (SFL) in a wireless network. The method includes receiving local split points associated with DNN model over a time period from client device (102) connected to edge device (101) for training the DNN model in the split federated learning and determining average of local split points associated with DNN model from client device over time period. Further the method discloses, determining global split point for partitioning the DNN model between client device (102) and the edge device (101) based on the average of the local split points and applying the determined global split point for partitioning the DNN model between the client device (102) and the edge device (101) to train the DNN model.

Inventors:
KARJEE JYOTIRMOY (IN)
S PRAVEEN NAIK (IN)
NAGARAJA RAO SRINIDHI (IN)
YIP ERIC HO CHING (KR)
CHAKRABORTY PRASENJIT (IN)
DABBIRU RAMESH BABU VENKAT (IN)
Application Number:
PCT/KR2023/005530
Publication Date:
November 02, 2023
Filing Date:
April 24, 2023
Export Citation:
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Assignee:
SAMSUNG ELECTRONICS CO LTD (KR)
International Classes:
G06N3/098; G06N3/08; G06N3/092; H04L41/16; H04L67/10; H04L67/59
Foreign References:
CN113657471A2021-11-16
CN113497785A2021-10-12
US20200311546A12020-10-01
CN114169537A2022-03-11
Other References:
ZHOU HONGBO, ZHANG WEIWEI, WANG CHENGWEI, MA XIN, YU HAORAN: "BBNet: A Novel Convolutional Neural Network Structure in Edge-Cloud Collaborative Inference", SENSORS, vol. 21, no. 13, pages 4494, XP093104643, DOI: 10.3390/s21134494
Attorney, Agent or Firm:
Y.P.LEE, MOCK & PARTNERS (KR)
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