Person

Anne-Marie Kermarrec

Related publications (52)

Smaller, Faster & Lighter KNN Graph Constructions

Rachid Guerraoui, Anne-Marie Kermarrec, Olivier Ruas

We propose GoldFinger, a new compact and fast-to-compute binary representation of datasets to approximate Jaccard’s index. We illustrate the effectiveness of GoldFinger on the emblematic big data problem of K-Nearest-Neighbor (KNN) graph construction and s ...

2020

Fingerprinting Big Data: The Case of KNN Graph Construction

Rachid Guerraoui, Anne-Marie Kermarrec, Olivier Ruas

We propose fingerprinting, a new technique that consists in constructing compact, fast-to-compute and privacy-preserving binary representations of datasets. We illustrate the effectiveness of our approach on the emblematic big data problem of K-Nearest-Nei ...

2019

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

Collaborative Filtering Under a Sybil Attack: Similarity Metrics do Matter!

Rachid Guerraoui, Anne-Marie Kermarrec, Davide Frey, Antoine Rault, Florestan Laurentin Marie De Moor

Recommendation systems help users identify interesting content, but they also open new privacy threats. In this paper, we deeply analyze the effect of a Sybil attack that tries to infer information on users from a user-based collaborative-filtering recomme ...

IEEE2018

Heterogeneous Recommendations: What You Might Like To Read After Watching Interstellar

Rachid Guerraoui, Anne-Marie Kermarrec, Tao Lin, Rhicheek Patra

Recommenders, as widely implemented nowadays by major e-commerce players like Netflix or Amazon, use collaborative filtering to suggest the most relevant items to their users. Clearly, the effectiveness of recommenders depends on the data they can exploit, ...

Assoc Computing Machinery2017

ProteusTM: Abstraction Meets Performance in Transactional Memory

Rachid Guerraoui, Anne-Marie Kermarrec, Paolo Romano, Diego Didona

The Transactional Memory (TM) paradigm promises to greatly simplify the development of concurrent applications. This led, over the years, to the creation of a plethora of TM implementations delivering wide ranges of performance across workloads. Yet, no un ...

2016

ProteusTM: Abstraction Meets Performance in Transactional Memory

Rachid Guerraoui, Anne-Marie Kermarrec, Diego Didona

Assoc Computing Machinery2016

Privacy-preserving distributed collaborative filtering

Rachid Guerraoui, Anne-Marie Kermarrec, Davide Frey

We propose a new mechanism to preserve privacy while leveraging user profiles in distributed recommender systems. Our mechanism relies on two contributions: (i) an original obfuscation scheme, and (ii) a randomized dissemination protocol. We show that our ...

Springer Wien2016

Atum: Scalable Group Communication Using Volatile Groups

Rachid Guerraoui, Anne-Marie Kermarrec, Dragos-Adrian Seredinschi, Matej Pavlovic

This paper presents Atum, a group communication middleware for a large, dynamic, and hostile environment. At the heart of Atum lies the novel concept of volatile groups: small, dynamic groups of nodes, each executing a state machine replication protocol, o ...

ACM Press2016

Hawk: Hybrid Datacenter Scheduling

Willy Zwaenepoel, Anne-Marie Kermarrec, Pamela Isabel Delgado Borda, Florin Dinu

This paper addresses the problem of efficient scheduling of large clusters under high load and heterogeneous workloads. A heterogeneous workload typically consists of many short jobs and a small number of large jobs that consume the bulk of the cluster's r ...

USENIX Association2015

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