Hello, since Nov. 2018, I am on an “advanced research position” at Inria, in the WIDE team. My current and main topics of research are
- the study of black-box algorithms in the context of recommender systems, and the related scalable computation
- algorithms for the distribution of machine learning (deep networks, GANs)
I was a senior research scientist at Technicolor R&I (2009-2018), where I worked on scalable storage, processing and machine learning for data analytics and monitoring of home devices. I own a PhD on distributed systems from University of Rennes 1, and a background on peer-to-peer systems, and graph mining/algorithms. My Ph.D. thesis was financed by Orange Labs (where I stayed btw 2004-2007). I obtained my habilitation (HDR) on November 2016 from University of Rennes 1. I am the president and sysadmin of the gozdata association, that provides the gozmail service, built from free software.
- Article from Algorithm Watch (Berlin) on our “bouncer problem” “Explainable AI” doesn’t work for online services – now there’s proof
- Atelier “algorithmes en boite-noire”, le 10 octobre 2019 à Lyon.
- Article Emergences/Inria “Plus de transparence pour les algorithmes de recommandation” par J-M Prima.
- Talk video about “Decision boundaries & security related questions” @ the Deep Learning : from theory to applications workshop in Sept. 2018 in Rennes: VIDEO HERE.
- Second order centrality code now part of the Networkx library v2.2.
The Bouncer Problem: Challenges to Remote Explainability, Erwan Le Merrer, Gilles Trédan. [ArXiv preprint 2019].
Adversarial Frontier Stitching for Remote Neural Network Watermarking, Erwan Le Merrer, Patrick Perez, Gilles Trédan. In the journal of Neural Computing and Applications, 2019. [editor]
TamperNN: Efficient Tampering Detection of Deployed Neural Nets, Erwan Le Merrer, Gilles Trédan. In ISSRE, 2019. [preprint]
Unified and Scalable Incremental Recommenders with Consumed Item Packs, Rachid Guerraoui, Erwan Le Merrer, Rhicheek Patra, Jean-Ronan Vigouroux. In Euro-par 2019. [preprint].
Application-aware adaptive partitioning for graph processing systems, Erwan Le Merrer, Gilles Trédan. (6p short) In MASCOTS 2019. [preprint]
MD-GAN: Multi-Discriminator Generative Adversarial Networks for Distributed Datasets, Corentin Hardy, Erwan Le Merrer, Bruno Sericola. In IPDPS, 2019. [preprint].
zoNNscan : a boundary-entropy index for zone inspection of neural models, Adel Jaouen, Erwan Le Merrer. [ArXiv preprint 2018].
Distributed deep learning on edge-devices: feasibility via adaptive compression, Corentin Hardy, Erwan Le Merrer, Bruno Sericola. In IEEE NCA, 2017. Best paper award [preprint].
The topological face of recommendation, Erwan Le Merrer, Gilles Trédan. In Complex Networks 2017. [preprint].
Uncovering Influence Cookbooks : Reverse Engineering the Topological Impact in Peer Ranking Services, Erwan Le Merrer, Gilles Trédan. In ACM CSCW, 2017. [preprint].
- Pushed non-randomness computation for graphs, by Ying & Wu, in NetworkX 2.4.
- zoNNscan code, for analysis of decision boundaries, available here.
- Second order centrality code now part of the Networkx library, from ComCom paper.
- Corentin’s code for distributed deep learning (NCA best paper) here and for random neural layers here.
- IEEE NCA 2017 best paper award, for paper “Distributed deep learning on edge-devices: feasibility via adaptive compression”, with Corentin Hardy and Bruno Sericola.
- Paper co-authors are awarded prize “La recherche 2015”, for work on cold storage, from Eurosys 2014.
- Prix “Bretagne jeune chercheur” 2011, mention spéciale.
As my main participation to scientific events, I was co-chair of Middleware 2018 industry track, in Rennes, and AlgoTel 2019 program co-chair. Co-organizing WOS with INRIA and Interdigital (ex Technicolor), a workshop on storage, cloud processing and data analytics, in every year Rennes: WOS archive.
I have co-authored 8 granted patents, and around 37 pending demands.