Publications

You can also find all my research works on my Google Scholar page.

Thesis

Asymptotically exact data augmentation – Models and Monte Carlo sampling with applications to Bayesian inference
Ph.D. thesis, Institut National Polytechnique de Toulouse, 2020
pdf

Preprints

1. Distribution-Aware Mean Estimation under User-level Local Differential Privacy
   C. Pla, H. Richard and M. Vono
   arXiv
   
   

Journal papers

1. Personalised Federated Learning On Heterogeneous Feature Spaces
   A. Rakotomamonjy, M. Vono, H. Jesse Medina Ruiz and L. Ralaivola
   Transactions on Machine Learning Research, to appear, 2024
   arXiv   doi
   
   
2. Gas kinematics around filamentary structures in the Orion B cloud
   M. Gaudel et al.
   Astronomy & Astrophysics, vol. 670, no. A59, February 2023
   arXiv   pdf   doi
   
   
3. Efficient MCMC sampling with dimension-free convergence rate using ADMM-type splitting
   M. Vono^*, D. Paulin^* and A. Doucet
   Journal of Machine Learning Research, vol. 23, no. 25, pp. 1-69, 2022
   arXiv   doi   Xian's blog post
   
   
4. High-dimensional Gaussian sampling: a review and a unifying approach based on a stochastic proximal point algorithm
   M. Vono, N. Dobigeon and P. Chainais
   SIAM Review, vol. 64, no. 1, pp. 3-56, 2022
   arXiv   pdf   doi   code
   
   
5. Asymptotically exact data augmentation: models, properties and algorithms
   M. Vono, N. Dobigeon and P. Chainais
   Journal of Computational and Graphical Statistics, vol. 30, no. 2, pp. 335-348, 2021
   arXiv   pdf   doi   code
   
   
6. Tracers of the ionization fraction in dense and translucent gas. I. Automated exploitation of massive astrochemical model grids
   E. Bron et al.
   Astronomy & Astrophysics, vol. 645, no. A28, January 2021
   arXiv   pdf   doi
   
   
7. Quantitative inference of the H2 column densities from 3 mm molecular emission: A case study towards Orion B
   P. Gratier et al.
   Astronomy & Astrophysics, vol. 645, no. A27, January 2021
   arXiv   pdf   doi
   
   
8. C18O, 13CO, and 12CO abundances and excitation temperatures in the Orion B molecular cloud
   A. Roueff et al.
   Astronomy & Astrophysics, vol. 645, no. A26, January 2021
   arXiv   pdf   doi
   
   
9. Split-and-augmented Gibbs sampler - Application to large-scale inference problems
   M. Vono, N. Dobigeon and P. Chainais
   IEEE Transactions on Signal Processing, vol. 67, no. 6, pp. 1648-1661, March 2019
   arXiv   pdf   doi   bibtex   code
   
   

International conference papers

1. DU-Shapley: A Shapley Value Proxy for Efficient Dataset Valuation
   F. Garrido-Lucero^*, B. Heymann^*, M. Vono^*, P. Loiseau and V. Perchet
   NeurIPS, Vancouver, Canada, 2024
   arXiv  
   
   
2. Position Paper: Open Research Challenges for Private Advertising Systems under Local Differential Privacy
   M. Tullii, S. Gaucher, H. Richard, E. Diemert, V. Perchet, A. Rakotomamonjy, C. Calauzènes and M. Vono
   WISE, Doha, Qatar, 2024
   arXiv  
   
   
3. FedPop: A Bayesian Approach for Personalised Federated Learning
   N. Kotelevskii^*, M. Vono^*, E. Moulines and A. Durmus
   NeurIPS, New Orleans, USA, 2022
   arXiv  
   
   
4. Mixture of noises and sampling of non-log-concave posterior distributions
   P. Palud et al.
   EUSIPCO, Belgrade, Serbia, 2022
   arXiv  
   
   
5. QLSD: Quantised Langevin stochastic dynamics for Bayesian federated learning
   M. Vono, V. Plassier, A. Durmus, A. Dieuleveut and E. Moulines
   AISTATS, Online, 2022
   arXiv
   
   
6. DG-LMC: a turn-key and scalable synchronous distributed MCMC algorithm via Langevin Monte Carlo within Gibbs
   V. Plassier^*, M. Vono^*, A. Durmus^* and E. Moulines
   ICML, Online, 2021 [Long talk, top 14% of accepted papers]
   arXiv   pdf   doi   bibtex   code
   
   
7. A fully Bayesian approach for inferring physical properties with credibility intervals from noisy astronomical data
   M. Vono et al.
   IEEE WHISPERS, Amsterdam, Netherlands, 2019
   pdf   doi   bibtex
   
   
8. Bayesian image restoration under Poisson noise and log-concave prior
   M. Vono, N. Dobigeon and P. Chainais
   IEEE ICASSP, Brighton, U.K., 2019
   pdf   doi   bibtex   code
   
   
9. Efficient sampling through variable splitting-inspired Bayesian hierarchical models
   M. Vono, N. Dobigeon and P. Chainais
   IEEE ICASSP, Brighton, U.K., 2019
   pdf   doi   bibtex   code
   
   
10. Sparse Bayesian binary logistic regression using the split-and-augmented Gibbs sampler
    M. Vono, N. Dobigeon and P. Chainais
    IEEE MLSP, Aalborg, Denmark, 2018 [Finalist for the Best Student Paper Award]
    pdf   doi   bibtex   code

National conference papers

1. Modèles augmentés asymptotiquement exacts
   M. Vono, N. Dobigeon and P. Chainais
   GRETSI, Lille, France, 2019
   pdf   bibtex
   
   
2. Un modèle augmenté asymptotiquement exact pour la restauration bayésienne d’images dégradées par un bruit de Poisson
   M. Vono, N. Dobigeon and P. Chainais
   GRETSI, Lille, France, 2019
   pdf   bibtex
   
   

^* indicates equal contribution.