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Maxime Vono

13 papers hereh-index 12404 citations22 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author5
  • middle author7

Across the 12 of 13 papers where every author was matched, so the position is known.

fields
  • astro-ph.GA4
  • cs.LG3
  • stat.ME3
  • stat.CO2
  • cs.AI1
same name
  • Maxime Vono — 3 papers, h 1
  • Maxime Vono — 1 paper, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20182023
most citedSplit-and-augmented Gibbs sampler - Application to large-scale inference problems

58 citations · 232 across the 13 of their papers we have counts for

collaborators
Showing cs.LGShow all

3 papers · 1 filter

cs.LG2023★ 6 cited

Personalised Federated Learning On Heterogeneous Feature Spaces

Alain Rakotomamonjy, Maxime Vono, Hamlet Jesse Medina Ruiz +1

Most personalised federated learning (FL) approaches assume that raw data of all clients are defined in a common subspace i.e. all clients store their data according to the same sc…

cs.LG2022★ 3 cited

FedPop: A Bayesian Approach for Personalised Federated Learning

Nikita Kotelevskii, Maxime Vono, Eric Moulines +1

Personalised federated learning (FL) aims at collaboratively learning a machine learning model taylored for each client. Albeit promising advances have been made in this direction,…

cs.LG2021★ 3 cited

QLSD: Quantised Langevin stochastic dynamics for Bayesian federated learning

Maxime Vono, Vincent Plassier, Alain Durmus +2

The objective of Federated Learning (FL) is to perform statistical inference for data which are decentralised and stored locally on networked clients. FL raises many constraints wh…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.