collaborators

17 papers

econ.TH2026

Algorithmic collusion under asynchronous price updating

Ivan Conjeaud, Gaspard Abel, Argyris Kalogeratos

This paper investigates the effect of asynchrony in agents' updates in the emergence of algorithmic collusion. We present a continuous-time model for algorithmic collusion in which…

stat.ML2026

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection

Gabriel Singer, Samuel Gruffaz, Olivier Vo Van +2

We study imbalanced crowdsourcing with a focus on class-dependent annotator accuracy, a setting that, to the best of our knowledge, remains relatively underexplored despite its imp…

cs.LG2026

Parametrized Power-Iteration Clustering for Directed Graphs

Gwendal Debaussart-Joniec, Harry Sevi, Matthieu Jonckheere +1

Vertex-level clustering for directed graphs (digraphs) remains challenging as edge directionality breaks the key assumptions underlying popular spectral methods, which also incur t…

cs.LG2026

Optimal Fair Aggregation of Crowdsourced Noisy Labels using Demographic Parity Constraints

Gabriel Singer, Samuel Gruffaz, Olivier Vo Van +2

As acquiring reliable ground-truth labels is usually costly, or infeasible, crowdsourcing and aggregation of noisy human annotations is the typical resort. Aggregating subjective l…

cs.LG2026

Cascaded Transfer: Learning Many Tasks under Budget Constraints

Eloi Campagne, Yvenn Amara-Ouali, Yannig Goude +2

In distributed applications, such as energy demand forecasting at the substation level or federated learning, a large number of related tasks must be learned by different models, w…

math.OC2026

GLOBe: A Modular Global Optimization library

Gaëtan Serré, Argyris Kalogeratos, Nicolas Vayatis

Open-source libraries are have a catalytic role in research pipelines, where new methods must be compared against up-to-date baselines. We present the GLobal Optimization Benchmark…