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2310.08087
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A Carbon Tracking Model for Federated Learning: Impact of Quantization
and Sparsification

v1v2 (latest)

A Carbon Tracking Model for Federated Learning: Impact of Quantization and Sparsification

IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (MDCLN), 2023

12 October 2023

ArXiv (abs)PDF HTML Github

Papers citing "A Carbon Tracking Model for Federated Learning: Impact of Quantization and Sparsification"

2 / 2 papers shown

Towards Heterogeneity-Aware and Energy-Efficient Topology Optimization for Decentralized Federated Learning in Edge Environment

Towards Heterogeneity-Aware and Energy-Efficient Topology Optimization for Decentralized Federated Learning in Edge Environment

108

1

0

01 Aug 2025

Compressed Bayesian Federated Learning for Reliable Passive Radio
Sensing in Industrial IoT

Compressed Bayesian Federated Learning for Reliable Passive Radio Sensing in Industrial IoTConference on Algebraic Informatics (CAI), 2024

327

1

0

09 May 2024

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