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The Cost of Training Machine Learning Models over Distributed Data
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v1v2 (latest)

The Cost of Training Machine Learning Models over Distributed Data Sources

IEEE Open Journal of the Communications Society (OJ-COMS), 2022
15 September 2022
Elia Guerra
F. Wilhelmi
M. Miozzo
Paolo Dini
    FedML
ArXiv (abs)PDFHTML

Papers citing "The Cost of Training Machine Learning Models over Distributed Data Sources"

12 / 12 papers shown
Characterizing the Multiclass Learnability of Forgiving 0-1 Loss Functions
Characterizing the Multiclass Learnability of Forgiving 0-1 Loss Functions
Jacob Trauger
Tyson Trauger
Ambuj Tewari
290
0
0
09 Oct 2025
Energy Consumption of TLS, Searchable Encryption and Fully Homomorphic Encryption
Energy Consumption of TLS, Searchable Encryption and Fully Homomorphic Encryption
Marc Damie
Mihai Pop
Merijn Posthuma
288
0
0
06 Aug 2025
Energy-Efficient Federated Learning for AIoT using Clustering Methods
Energy-Efficient Federated Learning for AIoT using Clustering MethodsIEEE Internet of Things Journal (IEEE IoT J.), 2025
Roberto Pereira
Fernanda Famá
Charalampos Kalalas
Paolo Dini
281
2
0
14 May 2025
Stratify: Rethinking Federated Learning for Non-IID Data through Balanced Sampling
Stratify: Rethinking Federated Learning for Non-IID Data through Balanced Sampling
Hui Yeok Wong
Chee Kau Lim
Chee Seng Chan
FedML
203
0
0
18 Apr 2025
Energy Minimization for Participatory Federated Learning in IoT Analyzed via Game Theory
Energy Minimization for Participatory Federated Learning in IoT Analyzed via Game TheoryDigital Signal Processing and Signal Processing Education Workshop (SPSPE), 2024
Alessandro Buratto
Elia Guerra
M. Miozzo
Paolo Dini
Leonardo Badia
238
4
0
27 Mar 2025
Feature Aggregation with Latent Generative Replay for Federated Continual Learning of Socially Appropriate Robot Behaviours
Feature Aggregation with Latent Generative Replay for Federated Continual Learning of Socially Appropriate Robot Behaviours
Nikhil Churamani
Saksham Checker
Fethiye Irmak Dogan
Hao-Tien Lewis Chiang
Hatice Gunes
FedML
498
4
0
24 Feb 2025
Evaluation of Bio-Inspired Models under Different Learning Settings For Energy Efficiency in Network Traffic Prediction
Evaluation of Bio-Inspired Models under Different Learning Settings For Energy Efficiency in Network Traffic PredictionInternational Journal of Neural Systems (IJNS), 2024
Theodoros Tsiolakis
Nikolaos Pavlidis
V. Perifanis
P. Efraimidis
451
0
0
23 Dec 2024
Learn More by Using Less: Distributed Learning with Energy-Constrained Devices
Learn More by Using Less: Distributed Learning with Energy-Constrained Devices
Roberto Pereira
Cristian J. Vaca-Rubio
Luis Blanco
FedML
341
0
0
03 Dec 2024
AQMLator -- An Auto Quantum Machine Learning E-Platform
AQMLator -- An Auto Quantum Machine Learning E-PlatformComputer Science (CS), 2024
Tomasz Rybotycki
Piotr Gawron
484
1
0
26 Sep 2024
Energy-Aware Decentralized Learning with Intermittent Model Training
Energy-Aware Decentralized Learning with Intermittent Model Training
Akash Dhasade
Paolo Dini
Elia Guerra
Anne-Marie Kermarrec
M. Miozzo
Rafael Pires
Rishi Sharma
M. Vos
287
2
0
01 Jul 2024
Towards Energy-Aware Federated Traffic Prediction for Cellular Networks
Towards Energy-Aware Federated Traffic Prediction for Cellular NetworksInternational Conference on Fog and Mobile Edge Computing (FMEC), 2023
V. Perifanis
Nikolaos Pavlidis
Selim F. Yilmaz
F. Wilhelmi
Elia Guerra
M. Miozzo
P. Efraimidis
Paolo Dini
R. Koutsiamanis
250
17
0
19 Sep 2023
Federated Learning for 5G Base Station Traffic Forecasting
Federated Learning for 5G Base Station Traffic Forecasting
V. Perifanis
Nikolaos Pavlidis
R. Koutsiamanis
P. Efraimidis
AI4TS
295
69
0
28 Nov 2022
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