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Federated Learning for Internet of Things: A Federated Learning
  Framework for On-device Anomaly Data Detection
v1v2v3v4 (latest)

Federated Learning for Internet of Things: A Federated Learning Framework for On-device Anomaly Data Detection

15 June 2021
Tuo Zhang
Chaoyang He
Tian-Shya Ma
Lei Gao
Mark Ma
Salman Avestimehr
    FedML
ArXiv (abs)PDFHTMLGithub (44★)

Papers citing "Federated Learning for Internet of Things: A Federated Learning Framework for On-device Anomaly Data Detection"

24 / 24 papers shown
C${}^2$Prompt: Class-aware Client Knowledge Interaction for Federated Continual Learning
C2{}^22Prompt: Class-aware Client Knowledge Interaction for Federated Continual Learning
Kunlun Xu
Yibo Feng
Jiangmeng Li
Yongsheng Qi
Jiahuan Zhou
CLLVLM
196
1
0
24 Sep 2025
An Adaptive Clustering Scheme for Client Selections in Communication-Efficient Federated Learning
An Adaptive Clustering Scheme for Client Selections in Communication-Efficient Federated LearningAsia-Pacific Conference on Wearable Computing Systems (AWCS), 2023
Yan-Ann Chen
Guan-Lin Chen
FedML
256
0
0
11 Apr 2025
HFedCKD: Toward Robust Heterogeneous Federated Learning via Data-free Knowledge Distillation and Two-way Contrast
Yiting Zheng
Bohan Lin
Jinqian Chen
Jihua Zhu
FedML
201
0
0
09 Mar 2025
QBI: Quantile-based Bias Initialization for Efficient Private Data
  Reconstruction in Federated Learning
QBI: Quantile-based Bias Initialization for Efficient Private Data Reconstruction in Federated Learning
Micha V. Nowak
Tim P. Bott
David Khachaturov
Frank Puppe
Adrian Krenzer
Amar Hekalo
FedML
163
1
0
26 Jun 2024
MicroPython Testbed for Federated Learning Algorithms
MicroPython Testbed for Federated Learning AlgorithmsTelecommunications Forum (TELFOR), 2024
Miroslav Popovic
M. Popovic
I. Kastelan
Miodrag Djukic
I. Basicevic
204
1
0
15 May 2024
Enhancing IoT Security Against DDoS Attacks through Federated Learning
Enhancing IoT Security Against DDoS Attacks through Federated Learning
Ghazaleh Shirvani
Saeid Ghasemshirazi
Mohammad Ali Alipour
336
4
0
16 Mar 2024
A Federated Learning Algorithms Development Paradigm
A Federated Learning Algorithms Development ParadigmEuropean Conference on the Engineering of Computer-Based Systems (ECBS), 2023
Miroslav Popovic
M. Popovic
I. Kastelan
Miodrag Djukic
I. Basicevic
222
6
0
08 Oct 2023
ProvLight: Efficient Workflow Provenance Capture on the Edge-to-Cloud
  Continuum
ProvLight: Efficient Workflow Provenance Capture on the Edge-to-Cloud ContinuumIEEE International Conference on Cluster Computing (CLUSTER), 2023
Daniel Rosendo
M. Mattoso
Alexandru Costan
Renan Souza
Débora B. Pina
P. Valduriez
Gabriel Antoniu
191
7
0
20 Jul 2023
Correct orchestration of Federated Learning generic algorithms:
  formalisation and verification in CSP
Correct orchestration of Federated Learning generic algorithms: formalisation and verification in CSPEuropean Conference on the Engineering of Computer-Based Systems (ECBS), 2023
Ivan Prokić
S. Ghilezan
Simona Kasterovic
M. Popovic
M. Popovic
I. Kastelan
FedML
259
8
0
26 Jun 2023
A Simple Python Testbed for Federated Learning Algorithms
A Simple Python Testbed for Federated Learning Algorithms
M. Popovic
M. Popovic
I. Kastelan
Miodrag Djukic
S. Ghilezan
FedML
234
14
0
31 May 2023
An Empirical Study of Federated Learning on IoT-Edge Devices: Resource
  Allocation and Heterogeneity
An Empirical Study of Federated Learning on IoT-Edge Devices: Resource Allocation and HeterogeneityIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023
Kok-Seng Wong
Manh Nguyen-Duc
Khiem Le-Huy
Long Ho-Tuan
Cuong Do-Danh
Danh Le-Phuoc
FedML
174
14
0
31 May 2023
TimelyFL: Heterogeneity-aware Asynchronous Federated Learning with
  Adaptive Partial Training
TimelyFL: Heterogeneity-aware Asynchronous Federated Learning with Adaptive Partial Training
Tuo Zhang
Lei Gao
Sunwoo Lee
Mi Zhang
Salman Avestimehr
FedML
236
50
0
14 Apr 2023
CADeSH: Collaborative Anomaly Detection for Smart Homes
CADeSH: Collaborative Anomaly Detection for Smart HomesIEEE Internet of Things Journal (IEEE IoT J.), 2023
Yair Meidan
D. Avraham
H. Libhaber
A. Shabtai
176
16
0
02 Mar 2023
QuantPipe: Applying Adaptive Post-Training Quantization for Distributed
  Transformer Pipelines in Dynamic Edge Environments
QuantPipe: Applying Adaptive Post-Training Quantization for Distributed Transformer Pipelines in Dynamic Edge EnvironmentsIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2022
Hong Wang
Connor Imes
Souvik Kundu
Peter A. Beerel
S. Crago
J. Walters
MQ
185
8
0
08 Nov 2022
Client Selection in Federated Learning: Principles, Challenges, and
  Opportunities
Client Selection in Federated Learning: Principles, Challenges, and OpportunitiesIEEE Internet of Things Journal (IEEE IoT J.), 2022
Lei Fu
Huan Zhang
Ge Gao
Mi Zhang
Xin Liu
FedML
285
218
0
03 Nov 2022
FedAudio: A Federated Learning Benchmark for Audio Tasks
FedAudio: A Federated Learning Benchmark for Audio TasksIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2022
Tuo Zhang
Tiantian Feng
Samiul Alam
Sunwoo Lee
Mi Zhang
Shrikanth S. Narayanan
Salman Avestimehr
FedML
283
30
0
27 Oct 2022
Symbolic analysis meets federated learning to enhance malware identifier
Symbolic analysis meets federated learning to enhance malware identifierARES (ARES), 2022
Khanh-Huu-The Dam
Charles-Henry Bertrand Van Ouytsel
Axel Legay
FedML
237
7
0
29 Apr 2022
When the Curious Abandon Honesty: Federated Learning Is Not Private
When the Curious Abandon Honesty: Federated Learning Is Not PrivateEuropean Symposium on Security and Privacy (EuroS&P), 2021
Franziska Boenisch
Adam Dziedzic
R. Schuster
Ali Shahin Shamsabadi
Ilia Shumailov
Nicolas Papernot
FedMLAAML
293
226
0
06 Dec 2021
FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks
FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks
Chaoyang He
Alay Dilipbhai Shah
Zhenheng Tang
Adarshan Naiynar Sivashunmugam
Keerti Bhogaraju
Mita Shimpi
Li Shen
Xiaowen Chu
Mahdi Soltanolkotabi
Salman Avestimehr
VLMFedML
234
81
0
22 Nov 2021
Federated Learning for Internet of Things: Applications, Challenges, and
  Opportunities
Federated Learning for Internet of Things: Applications, Challenges, and Opportunities
Tuo Zhang
Lei Gao
Chaoyang He
Mi Zhang
Bhaskar Krishnamachari
Salman Avestimehr
FedML
360
223
0
15 Nov 2021
LightSecAgg: a Lightweight and Versatile Design for Secure Aggregation
  in Federated Learning
LightSecAgg: a Lightweight and Versatile Design for Secure Aggregation in Federated Learning
Jinhyun So
Chaoyang He
Chien-Sheng Yang
Songze Li
Qian-long Yu
Ramy E. Ali
Başak Güler
Salman Avestimehr
FedML
353
227
0
29 Sep 2021
FedAdapt: Adaptive Offloading for IoT Devices in Federated Learning
FedAdapt: Adaptive Offloading for IoT Devices in Federated LearningIEEE Internet of Things Journal (IEEE IoT Journal), 2021
Di Wu
R. Ullah
P. Harvey
Peter Kilpatrick
I. Spence
Blesson Varghese
358
113
0
09 Jul 2021
From Distributed Machine Learning to Federated Learning: A Survey
From Distributed Machine Learning to Federated Learning: A SurveyKnowledge and Information Systems (KAIS), 2021
Ji Liu
Jizhou Huang
Yang Zhou
Xuhong Li
Shilei Ji
Haoyi Xiong
Dejing Dou
FedMLOOD
322
321
0
29 Apr 2021
Local Differential Privacy based Federated Learning for Internet of
  Things
Local Differential Privacy based Federated Learning for Internet of ThingsIEEE Internet of Things Journal (IEEE IoT J.), 2020
Yang Zhao
Jun Zhao
Mengmeng Yang
Teng Wang
Ning Wang
Lingjuan Lyu
Dusit Niyato
Kwok-Yan Lam
280
375
0
19 Apr 2020
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