4 citations · 11 across the 16 of their papers we have counts for
19 papers
IMILIA: interpretable multiple instance learning for inflammation prediction in IBD from H&E whole slide images
Thalyssa Baiocco-Rodrigues, Antoine Olivier, Reda Belbahri +7
As the therapeutic target for Inflammatory Bowel Disease (IBD) shifts toward histologic remission, the accurate assessment of microscopic inflammation has become increasingly centr…
Subgroup analysis methods for time-to-event outcomes in heterogeneous randomized controlled trials
Valentine Perrin, Nathan Noiry, Nicolas Loiseau +1
Non-significant randomized control trials can hide subgroups of good responders to experimental drugs, thus hindering subsequent development. Identifying such heterogeneous treatme…
Toward Stronger Textual Attack Detectors
Pierre Colombo, Marine Picot, Nathan Noiry +2
The landscape of available textual adversarial attacks keeps growing, posing severe threats and raising concerns regarding the deep NLP system's integrity. However, the crucial pro…
A Novel Information-Theoretic Objective to Disentangle Representations for Fair Classification
Pierre Colombo, Nathan Noiry, Guillaume Staerman +1
One of the pursued objectives of deep learning is to provide tools that learn abstract representations of reality from the observation of multiple contextual situations. More preci…
A Functional Data Perspective and Baseline On Multi-Layer Out-of-Distribution Detection
Eduardo Dadalto, Pierre Colombo, Guillaume Staerman +2
A key feature of out-of-distribution (OOD) detection is to exploit a trained neural network by extracting statistical patterns and relationships through the multi-layer classifier…
Online Matching in Geometric Random Graphs
Flore Sentenac, Nathan Noiry, Matthieu Lerasle +2
We investigate online maximum cardinality matching, a central problem in ad allocation. In this problem, users are revealed sequentially, and each new user can be paired with any p…
Towards More Robust NLP System Evaluation: Handling Missing Scores in Benchmarks
Anas Himmi, Ekhine Irurozki, Nathan Noiry +2
The evaluation of natural language processing (NLP) systems is crucial for advancing the field, but current benchmarking approaches often assume that all systems have scores availa…
Beyond Mahalanobis-Based Scores for Textual OOD Detection
Pierre Colombo, Eduardo D. C. Gomes, Guillaume Staerman +2
Deep learning methods have boosted the adoption of NLP systems in real-life applications. However, they turn out to be vulnerable to distribution shifts over time which may cause s…
Mitigating Gender Bias in Face Recognition Using the von Mises-Fisher Mixture Model
Jean-Rémy Conti, Nathan Noiry, Vincent Despiegel +2
In spite of the high performance and reliability of deep learning algorithms in a wide range of everyday applications, many investigations tend to show that a lot of models exhibit…
The Glass Ceiling of Automatic Evaluation in Natural Language Generation
Pierre Colombo, Maxime Peyrard, Nathan Noiry +2
Automatic evaluation metrics capable of replacing human judgments are critical to allowing fast development of new methods. Thus, numerous research efforts have focused on crafting…
Learning Disentangled Textual Representations via Statistical Measures of Similarity
Pierre Colombo, Guillaume Staerman, Nathan Noiry +1
When working with textual data, a natural application of disentangled representations is fair classification where the goal is to make predictions without being biased (or influenc…
Learning to Rank Anomalies: Scalar Performance Criteria and Maximization of Two-Sample Rank Statistics
Myrto Limnios, Nathan Noiry, Stéphan Clémençon
The ability to collect and store ever more massive databases has been accompanied by the need to process them efficiently. In many cases, most observations have the same behavior,…
Online Matching in Sparse Random Graphs: Non-Asymptotic Performances of Greedy Algorithm
Nathan Noiry, Flore Sentenac, Vianney Perchet
Motivated by sequential budgeted allocation problems, we investigate online matching problems where connections between vertices are not i.i.d., but they have fixed degree distribu…
Long induced paths in a configuration model
Nathanaël Enriquez, Gabriel Faraud, Laurent Ménard +1
In an article published in 1987 in Combinatorica \cite{MR918397}, Frieze and Jackson established a lower bound on the length of the longest induced path (and cycle) in a sparse ran…
Large deviations for spectral measures of some spiked matrices
Nathan Noiry, Alain Rouault
We prove large deviations principles for spectral measures of perturbed (or spiked) matrix models in the direction of an eigenvector of the perturbation. In each model under study,…
A solvable class of renewal processes
Nathanaël Enriquez, Nathan Noiry
When the distribution of the inter-arrival times of a renewal process is a mixture of geometric laws, we prove that the renewal function of the process is given by the moments of a…
Depth First Exploration of a Configuration Model
Nathanaël Enriquez, Gabriel Faraud, Laurent Ménard +1
We introduce an algorithm that constructs a random uniform graph with prescribed degree sequence together with a depth first exploration of it. In the so-called supercritical regim…
Spectral Measures of Spiked Random Matrices
Nathan Noiry
We study two spiked models of random matrices under general frameworks corresponding respectively to additive deformation of random symmetric matrices and multiplicative perturbati…
Spectra of Wishart Matrices with size-dependent entries
Nathan Noiry
We prove the convergence of the empirical spectral measure of Wishart matrices with size-dependent entries and characterize the limiting law by its moments. We apply our result to…