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Anne-Marie Kermarrec

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Related publications (63)

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Get More for Less in Decentralized Learning Systems

Anne-Marie Kermarrec, Rafael Pereira Pires, Rishi Sharma, Akash Balasaheb Dhasade, Milos Vujasinovic

Decentralized learning (DL) systems have been gaining popularity because they avoid raw data sharing by communicating only model parameters, hence preserving data confidentiality. However, the large size of deep neural networks poses a significant challeng ...

IEEE2023

The Universal Gossip Fighter

Rachid Guerraoui, Anne-Marie Kermarrec, Rafaël Benjamin Pinot, Anastasiia Kucherenko

The notion of adversary is a staple of distributed computing. An adversary typically models “hostile” assumptions about the underlying distributed environment, e.g., a network that can drop messages, an operating system that can delay processes or an attac ...

IEEE2022

Energy-Aware Decentralized Learning with Intermittent Model Training

Anne-Marie Kermarrec, Rafael Pereira Pires, Rishi Sharma, Marinus Abraham de Vos, Akash Balasaheb Dhasade

SKIPTRAIN is a novel Decentralized Learning (DL) algorithm, which minimizes energy consumption in decentralized learning by strategically skipping some training rounds and substituting them with synchronization rounds. These trainingsilent periods, besides ...

IEEE2024

Noiseless Privacy-Preserving Decentralized Learning

Anne-Marie Kermarrec, Rafael Pereira Pires, Rishi Sharma, Marinus Abraham de Vos, Sayan Biswas

Decentralized learning (DL) enables collaborative learning without a server and without training data leaving the users' devices. However, the models shared in DL can still be used to infer training data. Conventional defenses such as differential privacy ...

Privacy Enhancing Technologies Symposium Advisory Board2024

Efficient Pyramidal Analysis of Gigapixel Images on a Decentralized Modest Computer Cluster

Anne-Marie Kermarrec, Rafael Pereira Pires, Rishi Sharma

Analyzing gigapixel images is recognized as computationally demanding. In this paper, we introduce PyramidAI, a technique for analyzing gigapixel images with reduced computational cost. The proposed approach adopts a gradual analysis of the image, beginnin ...

Springer Nature Switzerland2025

Personalizing Top-k Processing Online in a Peer-to-Peer Social Tagging Network

Rachid Guerraoui, Anne-Marie Kermarrec

The rapidly increasing amount of user-generated content in social tagging systems provides a huge source of information. Yet, performing effective search in these systems is very challenging, especially when we seek the most appropriate items that match a ...

Assoc Computing Machinery2014

WHATSUP: A Decentralized Instant News Recommender

Rachid Guerraoui, Anne-Marie Kermarrec

We present WhatsUp, a collaborative filtering system for disseminating news items in a large-scale dynamic setting with no central authority. WhatsUp constructs an implicit social network based on user profiles that express the opinions of users about the ...

2013

Cluster-and-Conquer: When Randomness Meets Graph Locality

Anne-Marie Kermarrec

K-Nearest-Neighbors (KNN) graphs are central to many emblematic data mining and machine-learning applications. Some of the most efficient KNN graph algorithms are incremental and local: they start from a random graph, which they incrementally improve by tr ...

IEEE COMPUTER SOC2021

FeGAN: Scaling Distributed GANs

Rachid Guerraoui, Anne-Marie Kermarrec, Arsany Hany Abdelmessih Guirguis

Existing approaches to distribute Generative Adversarial Networks (GANs) either (i) fail to scale for they typically put the two components of a GAN (the generator and the discriminator) on different machines, inducing significant communication overhead, o ...

2020

Epidemic Learning: Boosting Decentralized Learning with Randomized Communication

Rachid Guerraoui, Anne-Marie Kermarrec, Rafael Pereira Pires, Rishi Sharma, Marinus Abraham de Vos, Sadegh Farhadkhani

We present Epidemic Learning ( EL ), a simple yet powerful decentralized learning (DL) algorithm that leverages changing communication topologies to achieve faster model convergence compared to conventional DL approaches. At each round of EL, each node sen ...

2023

Privacy-Preserving Distributed Collaborative Filtering

Rachid Guerraoui, Anne-Marie Kermarrec

We propose a new mechanism to preserve privacy while leveraging user profiles in distributed recommender systems. Our mechanism relies on (i) an original obfuscation scheme to hide the exact profiles of users without significantly decreasing their utility, ...

Springer International Publishing2014

FLEET: Online Federated Learning via Staleness Awareness and Performance Prediction

Rachid Guerraoui, Anne-Marie Kermarrec, Rhicheek Patra

Federated learning (FL) is very appealing for its privacy benefits: essentially, a global model is trained with updates computed on mobile devices while keeping the data of users local. Standard FL infrastructures are however designed to have no energy or ...

ASSOC COMPUTING MACHINERY2022

Scalable and Secure Polling in Dynamic Distributed Networks

Rachid Guerraoui, Anne-Marie Kermarrec, Hamza Harkous, Florian Huc

We consider the problem of securely conducting a poll in synchronous dynamic networks equipped with a Public Key Infrastructure (PKI). Whereas previous distributed solutions had a communication cost of O(n^2) in an n nodes system, we present SPP (Secure an ...

2012

On Tracking Freeriders in Gossip Protocols

Rachid Guerraoui, Anne-Marie Kermarrec, Kévin Clément Huguenin, Maxime Monod

Peer-to-peer content dissemination applications suffer immensely from freeriders, i.e., nodes that do not provide their fair share. The Tit-for-Tat (TfT) incentives have received much attention as they help make such systems more robust against freeriding. ...

2009

Distributed Churn Measurement for Arbitrary Networks

Anne-Marie Kermarrec, Vincent Gramoli

ACM2008

Revisiting Ensembling in One-Shot Federated Learning

Rachid Guerraoui, Anne-Marie Kermarrec, Nirupam Gupta, Rafaël Benjamin Pinot, Rafael Pereira Pires, Rishi Sharma, Youssef Allouah, Akash Balasaheb Dhasade

Federated learning (FL) is an appealing approach to training machine learning models without sharing raw data. However, standard FL algorithms are iterative and thus induce a significant communication cost. One-shot federated learning (OFL) trades the iter ...

Curran Associates, Inc.2024

The Fake News Vaccine

Rachid Guerraoui, Willy Zwaenepoel, Anne-Marie Kermarrec, Alexandre David Olivier Maurer, Matej Pavlovic, Oana Maria Balmau

While spreading fake news is an old phenomenon, today social media enables misinformation to instantaneously reach millions of people. Content-based approaches to detect fake news, typically based on automatic text checking, are limited. It is indeed diffi ...

2019

Stretching Gossip with Live Streaming

Rachid Guerraoui, Anne-Marie Kermarrec, Maxime Monod

Gossip-based information dissemination protocols are considered easy to deploy, scalable and resilient to network dynamics. They are also considered highly ﬂexible, namely tunable at will to increase their robustness and adapt to churn. So far however, the ...

2009

The Utility and Privacy Effects of a Click

Rachid Guerraoui, Anne-Marie Kermarrec, Mahsa Taziki

2017

Brief Announcement: Towards Secured Distributed Polling in Social Networks

Rachid Guerraoui, Anne-Marie Kermarrec, Kévin Clément Huguenin, Maxime Monod

Springer-Verlag New York, Ms Ingrid Cunningham, 175 Fifth Ave, New York, Ny 10010 Usa2009