7 citations · 9 across the 7 of their papers we have counts for
10 papers
WattLayer: Get Layers Right to Estimate Inference Energy of Neural Networks
Adrien Sardi, Marie-Line Alberi Morel, Sara Alouf +2
The widespread adoption of Artificial Intelligence (AI) has led to increasing concerns about energy consumption, yet there is a lack of standardized methodologies to accurately est…
Small is Sufficient: Reducing the World AI Energy Consumption Through Model Selection
Tiago da Silva Barros, Frédéric Giroire, Ramon Aparicio-Pardo +1
The energy consumption and carbon footprint of Artificial Intelligence (AI) have become critical concerns due to rising costs and environmental impacts. In response, a new trend in…
Attribute Inference Attacks for Federated Regression Tasks
Francesco Diana, Othmane Marfoq, Chuan Xu +3
Federated Learning (FL) enables multiple clients, such as mobile phones and IoT devices, to collaboratively train a global machine learning model while keeping their data localized…
Local Model Reconstruction Attacks in Federated Learning and their Uses
Ilias Driouich, Chuan Xu, Giovanni Neglia +2
In this paper, we initiate the study of local model reconstruction attacks for federated learning, where a honest-but-curious adversary eavesdrops the messages exchanged between a…
Preferential attachment hypergraph with vertex deactivation
Frédéric Giroire, Nicolas Nisse, Kostiantyn Ohulchanskyi +2
In the field of complex networks, hypergraph models have so far received significantly less attention than graphs. However, many real-life networks feature multiary relations (co-a…
Revisiting the Random Subset Sum problem
Arthur da Cunha, Francesco d'Amore, Frédéric Giroire +3
The average properties of the well-known Subset Sum Problem can be studied by the means of its randomised version, where we are given a target value , random variables $X_1, \ld…
Preferential attachment hypergraph with high modularity
Frédéric Giroire, Nicolas Nisse, Thibaud Trolliet +1
Numerous works have been proposed to generate random graphs preserving the same properties as real-life large scale networks. However, many real networks are better represented by…
Interest Clustering Coefficient: a New Metric for Directed Networks like Twitter
Thibaud Trolliet, Nathann Cohen, Frédéric Giroire +2
We study here the clustering of directed social graphs. The clustering coefficient has been introduced to capture the social phenomena that a friend of a friend tends to be my frie…
A Random Growth Model with any Real or Theoretical Degree Distribution
Thibaud Trolliet, Frédéric Giroire, Stéphane Pérennes
The degree distributions of complex networks are usually considered to be power law. However, it is not the case for a large number of them. We thus propose a new model able to bui…
Energy Efficient Routing by Switching-Off Network Interfaces
Frédéric Giroire, Dorian Mazauric, Joanna Moulierac
Several studies exhibit that the traffic load of the routers only has a small influence on their energy consumption. Hence, the power consumption in networks is strongly related to…