91 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Institut national de recherche en sciences et technologies du numériqueFR5 papers
- Université de LilleFR4 papers
- Centre Inria de l'Université de LilleFR3 papers
- Laboratoire Traitement et Communication de l’InformationFR3 papers
- Centre National de la Recherche ScientifiqueFR2 papers
- Aalto UniversityFI1 paper
- Centre de Recherche en InformatiqueFR1 paper
- Centre de Recherche en Informatique, Signal et Automatique de LilleFR1 paper
- Czech Academy of Sciences, Institute of MathematicsCZ1 paper
- Data Management (Italy)IT1 paper
- Département de mathématiques et applicationsFR1 paper
- Département d'InformatiqueFR1 paper
15 papers
Anaphora Resolution in Dialogue: System Description (CODI-CRAC 2022 Shared Task)
Tatiana Anikina, Natalia Skachkova, Joseph Renner +1
We describe three models submitted for the CODI-CRAC 2022 shared task. To perform identity anaphora resolution, we test several combinations of the incremental clustering approach…
tasksource: A Dataset Harmonization Framework for Streamlined NLP Multi-Task Learning and Evaluation
Damien Sileo
The HuggingFace Datasets Hub hosts thousands of datasets, offering exciting opportunities for language model training and evaluation. However, datasets for a specific task type oft…
Linear Programs with Conjunctive Database Queries
Florent Capelli, Nicolas Crosetti, Joachim Niehren +1
In this paper, we study the problem of optimizing a linear program whose variables are the answers to a conjunctive query. For this we propose the language LP(CQ) for specifying li…
High-Dimensional Private Empirical Risk Minimization by Greedy Coordinate Descent
Paul Mangold, Aurélien Bellet, Joseph Salmon +1
In this paper, we study differentially private empirical risk minimization (DP-ERM). It has been shown that the worst-case utility of DP-ERM reduces polynomially as the dimension i…
Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging
Edwige Cyffers, Mathieu Even, Aurélien Bellet +1
Decentralized optimization is increasingly popular in machine learning for its scalability and efficiency. Intuitively, it should also provide better privacy guarantees, as nodes o…
The VoicePrivacy 2022 Challenge Evaluation Plan
Natalia Tomashenko, Xin Wang, Xiaoxiao Miao +7
For new participants - Executive summary: (1) The task is to develop a voice anonymization system for speech data which conceals the speaker's voice identity while protecting lingu…
MaxHedge: Maximising a Maximum Online
Stephen Pasteris, Fabio Vitale, Kevin Chan +2
We introduce a new online learning framework where, at each trial, the learner is required to select a subset of actions from a given known action set. Each action is associated wi…
A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization
Robin Vogel, Aurélien Bellet, Stéphan Clémençon
The performance of many machine learning techniques depends on the choice of an appropriate similarity or distance measure on the input space. Similarity learning (or metric learni…
A Distributed Frank-Wolfe Framework for Learning Low-Rank Matrices with the Trace Norm
Wenjie Zheng, Aurélien Bellet, Patrick Gallinari
We consider the problem of learning a high-dimensional but low-rank matrix from a large-scale dataset distributed over several machines, where low-rankness is enforced by a convex…
Decentralized Collaborative Learning of Personalized Models over Networks
Paul Vanhaesebrouck, Aurélien Bellet, Marc Tommasi
We consider a set of learning agents in a collaborative peer-to-peer network, where each agent learns a personalized model according to its own learning objective. The question add…
On the Troll-Trust Model for Edge Sign Prediction in Social Networks
Géraud Le Falher, Nicolò Cesa-Bianchi, Claudio Gentile +1
In the problem of edge sign prediction, we are given a directed graph (representing a social network), and our task is to predict the binary labels of the edges (i.e., the positive…
Extending Gossip Algorithms to Distributed Estimation of U-Statistics
Igor Colin, Aurélien Bellet, Joseph Salmon +1
Efficient and robust algorithms for decentralized estimation in networks are essential to many distributed systems. Whereas distributed estimation of sample mean statistics has bee…
Metric learning approach for graph-based label propagation
Pauline Wauquier, Mikaela Keller
The efficiency of graph-based semi-supervised algorithms depends on the graph of instances on which they are applied. The instances are often in a vectorial form before a graph lin…
On the Bernstein-Hoeffding method
Christos Pelekis, Jan Ramon, Yuyi Wang
We show that the Bernstein-Hoeffding method can be employed to a larger class of generalized moments. This class includes the exponential moments whose properties play a key role i…
Scaling-up Empirical Risk Minimization: Optimization of Incomplete U-statistics
Stéphan Clémençon, Aurélien Bellet, Igor Colin
In a wide range of statistical learning problems such as ranking, clustering or metric learning among others, the risk is accurately estimated by -statistics of degree …