activity
20162026
most citedConvergence rate of a simulated annealing algorithm with noisy observations

16 citations · 20 across the 7 of their papers we have counts for

collaborators

7 papers

stat.OT2026

Deepest voting on rankings

Jean-Baptiste Aubin, Antoine Rolland, Ioana Gavra +2

This article aims to present a unified framework for ranking-based voting rules based on the use of depth functions on permutations, as a counterpart of deepest voting rules on eva…

stat.ME2025

Optimal Transport-Based Clustering of Attributed Graphs with an Application to Road Traffic Data

Ioana Gavra, Ketsia Guichard-Sustowski, Loïc Le Marrec

In many real-world contexts, such as social or transport networks, data exhibit both structural connectivity and node-level attributes. For example, roads in a transport network ca…

math.ST2022

Parametric Lie group structures on the probabilistic simplex and generalized Compositional Data

Petre Birtea, Ioana Gavra

In this paper we build a set of parametric quotient Lie group structures on the probabilistic simplex that can be extended to real vector space structures. In particular, we redisc…

stat.ML2020★ 3 cited

Asymptotic study of stochastic adaptive algorithm in non-convex landscape

Sébastien Gadat, Ioana Gavra

This paper studies some asymptotic properties of adaptive algorithms widely used in optimization and machine learning, and among them Adagrad and Rmsprop, which are involved in mos…

math.PR2018

Online Barycenter Estimation of Large Weighted Graphs

Ioana Gavra, Laurent Risser

In this paper, we propose a new method to compute the barycenter of large weighted graphs endowed with probability measures on their nodes. We suppose that the edge weights are dis…

stat.ML2017★ 16 cited

Convergence rate of a simulated annealing algorithm with noisy observations

Clément Bouttier, Ioana Gavra

In this paper we propose a modified version of the simulated annealing algorithm for solving a stochastic global optimization problem. More precisely, we address the problem of fin…

math.PR2016★ 1 cited

How to compute the barycenter of a weighted graph

Sébastien Gadat, Ioana Gavra, Laurent Risser

Discrete structures like graphs make it possible to naturally and flexibly model complex phenomena. Since graphs that represent various types of information are increasingly availa…