no code implementations • 18 Mar 2024 • Sayan Biswas, Davide Frey, Romaric Gaudel, Anne-Marie Kermarrec, Dimitri Lerévérend, Rafael Pires, Rishi Sharma, François Taïani
This paper introduces ZIP-DL, a novel privacy-aware decentralized learning (DL) algorithm that relies on adding correlated noise to each model update during the model training process.
no code implementations • 19 Dec 2023 • Gwladys Kelodjou, Laurence Rozé, Véronique Masson, Luis Galárraga, Romaric Gaudel, Maurice Tchuente, Alexandre Termier
Among these methods, Kernel SHAP is widely used due to its model-agnostic nature and its well-founded theoretical framework.
no code implementations • 2 Aug 2022 • Camille-Sovanneary Gauthier, Romaric Gaudel, Elisa Fromont
The semi-bandit version, where a full matching is sampled at each iteration, has been addressed by \cite{ADMA}, creating an algorithm with an expected regret matching $O(\frac{L\log(L)}{\Delta}\log(T))$ with $2L$ players, $T$ iterations and a minimum reward gap $\Delta$.
no code implementations • 2 Aug 2022 • Romaric Gaudel, Matthieu Rodet
The semi-bandit version, where a full matching is sampled at each iteration, has been addressed by \cite{ADMA}, creating an algorithm with an expected regret matching $O(\frac{L\log(L)}{\Delta}\log(T))$ with $2L$ players, $T$ iterations and a minimum reward gap $\Delta$.
no code implementations • 2 Aug 2022 • Romaric Gaudel, Luis Galárraga, Julien Delaunay, Laurence Rozé, Vaishnavi Bhargava
The benefit of locality is one of the major premises of LIME, one of the most prominent methods to explain black-box machine learning models.
no code implementations • 28 Sep 2020 • Camille-Sovanneary Gauthier, Romaric Gaudel, Elisa Fromont
Multiple-play bandits aim at displaying relevant items at relevant positions on a web page.
4 code implementations • 24 Jun 2016 • Florian Strub, Romaric Gaudel, Jérémie Mary
A standard model for Recommender Systems is the Matrix Completion setting: given partially known matrix of ratings given by users (rows) to items (columns), infer the unknown ratings.
Ranked #1 on Recommendation Systems on Douban
1 code implementation • 2 Mar 2016 • Florian Strub, Jeremie Mary, Romaric Gaudel
Such algorithms look for latent variables in a large sparse matrix of ratings.
no code implementations • 25 Aug 2015 • Charanpal Dhanjal, Romaric Gaudel, Stephan Clemencon
With this in mind, we propose a class of objective functions over matrix factorisations which primarily represent a smooth surrogate for the real AUC, and in a special case we show how to prioritise the top of the list.
no code implementations • 10 Jul 2014 • Jérémie Mary, Romaric Gaudel, Preux Philippe
Finally, experimental evidence confirm that our algorithm is effective in dealing with the cold start problem on publicly available datasets.
no code implementations • 10 Jan 2014 • Charanpal Dhanjal, Romaric Gaudel, Stéphan Clémençon
It is the main goal of this paper to propose a novel method to perform matrix completion on-line.
no code implementations • 7 Jan 2013 • Charanpal Dhanjal, Romaric Gaudel, Stéphan Clémençon
Namely, the method promoted in this article can be viewed as an incremental eigenvalue solution for the spectral clustering method described by Ng.
no code implementations • International Conference on Machine Learning 2010 2010 • Romaric Gaudel, Michèle Sebag
This paper formalizes Feature Selection as a Reinforcement Learning problem, leading to a provably optimal though intractable selection policy.