9 citations · 25 across the 39 of their papers we have counts for
13 papers · 1 filter
On the Calibration of Crowdsourcing Aggregators
Gabriel Singer, Reda Arab, Maïssa Frikha +4
Calibration has been extensively studied for classifiers, but remains largely unexplored for crowdsourcing aggregation methods, which are increasingly used for making probabilistic…
A Finslerian Approach for Embedding Directed Data
Gwendal Debaussart-Joniec, Théau Blanchard, Argyris Kalogeratos
Many datasets carry an intrinsic directionality: citations point backward in time, cells differentiate along lineages, and traffic follows preferred routes. Spectral embedding meth…
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…
Collaborative non-parametric two-sample testing
Alejandro de la Concha, Nicolas Vayatis, Argyris Kalogeratos
This paper addresses the multiple two-sample test problem in a graph-structured setting, which is a common scenario in fields such as Spatial Statistics and Neuroscience. Each node…
Online non-parametric likelihood-ratio estimation by Pearson-divergence functional minimization
Alejandro de la Concha, Nicolas Vayatis, Argyris Kalogeratos
Quantifying the difference between two probability density functions, and , using available data, is a fundamental problem in Statistics and Machine Learning. A usual approa…
A framework for paired-sample hypothesis testing for high-dimensional data
Ioannis Bargiotas, Argyris Kalogeratos, Nicolas Vayatis
The standard paired-sample testing approach in the multidimensional setting applies multiple univariate tests on the individual features, followed by p-value adjustments. Such an a…
Online Centralized Non-parametric Change-point Detection via Graph-based Likelihood-ratio Estimation
Alejandro de la Concha, Argyris Kalogeratos, Nicolas Vayatis
Consider each node of a graph to be generating a data stream that is synchronized and observed at near real-time. At a change-point , a change occurs at a subset of nodes , w…
Collaborative likelihood-ratio estimation over graphs
Alejandro de la Concha, Nicolas Vayatis, Argyris Kalogeratos
Assuming we have iid observations from two unknown probability density functions (pdfs), and , the likelihood-ratio estimation (LRE) is an elegant approach to compare the tw…
Generalized Dirichlet Energy and Graph Laplacians for Clustering Directed and Undirected Graphs
Harry Sevi, Gwendal Debaussart-Joniec, Malik Hacini +2
Clustering in directed graphs remains a fundamental challenge due to the asymmetry in edge connectivity, which limits the applicability of classical spectral methods originally des…
Online non-parametric change-point detection for heterogeneous data streams observed over graph nodes
Alejandro de la Concha, Argyris Kalogeratos, Nicolas Vayatis
Consider a heterogeneous data stream being generated by the nodes of a graph. The data stream is in essence composed by multiple streams, possibly of different nature that depends…
Learning the piece-wise constant graph structure of a varying Ising model
Batiste Le Bars, Pierre Humbert, Argyris Kalogeratos +1
This work focuses on the estimation of multiple change-points in a time-varying Ising model that evolves piece-wise constantly. The aim is to identify both the moments at which sig…
A Spectral Method for Activity Shaping in Continuous-Time Information Cascades
Kevin Scaman, Argyris Kalogeratos, Luca Corinzia +1
Information Cascades Model captures dynamical properties of user activity in a social network. In this work, we develop a novel framework for activity shaping under the Continuous-…
Multivariate Hawkes Processes for Large-scale Inference
Rémi Lemonnier, Kevin Scaman, Argyris Kalogeratos
In this paper, we present a framework for fitting multivariate Hawkes processes for large-scale problems both in the number of events in the observed history and the number of…