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cs.LG2026
Exposing the Cost of Deep Learning Audio Development
Constance Douwes, Paul Magron, Romain Serizel
The environmental impact of deep learning has attracted increasing attention over the past decade. Existing studies mainly focus on the energy and carbon emissions of model trainin…
cs.LG2024
Normalizing Energy Consumption for Hardware-Independent Evaluation
Constance Douwes, Romain Serizel
The increasing use of machine learning (ML) models in signal processing has raised concerns about their environmental impact, particularly during resource-intensive training phases…
cs.LG2024
From Computation to Consumption: Exploring the Compute-Energy Link for Training and Testing Neural Networks for SED Systems
Constance Douwes, Romain Serizel
The massive use of machine learning models, particularly neural networks, has raised serious concerns about their environmental impact. Indeed, over the last few years we have seen…