Search Results - "Vono, Maxime"

Split-and-Augmented Gibbs Sampler-Application to Large-Scale Inference Problems by Vono, Maxime, Dobigeon, Nicolas, Chainais, Pierre

“…This paper derives two new optimization-driven Monte Carlo algorithms inspired from variable splitting and data augmentation. In particular, the formulation of…”
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Asymptotically Exact Data Augmentation: Models, Properties, and Algorithms by Vono, Maxime, Dobigeon, Nicolas, Chainais, Pierre

“…Data augmentation, by the introduction of auxiliary variables, has become an ubiquitous technique to improve convergence properties, simplify the…”
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Bayesian Image Restoration under Poisson Noise and Log-concave Prior by Vono, Maxime, Dobigeon, Nicolas, Chainais, Pierre

“…In recent years, much research has been devoted to the restoration of Poissonian images using optimization-based methods. On the other hand, the derivation of…”
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Efficient Sampling through Variable Splitting-inspired Bayesian Hierarchical Models by Vono, Maxime, Dobigeon, Nicolas, Chainais, Pierre

“…Markov chain Monte Carlo (MCMC) methods are an important class of computation techniques to solve Bayesian inference problems. Much recent research has been…”
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Distribution-Aware Mean Estimation under User-level Local Differential Privacy by Pla, Corentin, Richard, Hugo, Vono, Maxime

“…We consider the problem of mean estimation under user-level local differential privacy, where $n$ users are contributing through their local pool of data…”
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SPARSE BAYESIAN BINARY LOGISTIC REGRESSION USING THE SPLIT-AND-AUGMENTED GIBBS SAMPLER by Vono, Maxime, Dobigeon, Nicolas, Chainais, Pierre

“…Logistic regression has been extensively used to perform classification in machine learning and signal/image processing. Bayesian formulations of this model…”
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Personalised Federated Learning On Heterogeneous Feature Spaces by Rakotomamonjy, Alain, Vono, Maxime, Ruiz, Hamlet Jesse Medina, Ralaivola, Liva

“…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…”
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FedPop: A Bayesian Approach for Personalised Federated Learning by Kotelevskii, Nikita, Vono, Maxime, Moulines, Eric, Durmus, Alain

“…Personalised federated learning (FL) aims at collaboratively learning a machine learning model taylored for each client. Albeit promising advances have been…”
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High-dimensional Gaussian sampling: a review and a unifying approach based on a stochastic proximal point algorithm by Vono, Maxime, Dobigeon, Nicolas, Chainais, Pierre

“…Efficient sampling from a high-dimensional Gaussian distribution is an old but high-stake issue. Vanilla Cholesky samplers imply a computational cost and…”
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Asymptotically exact data augmentation: models, properties and algorithms by Vono, Maxime, Dobigeon, Nicolas, Chainais, Pierre

“…Data augmentation, by the introduction of auxiliary variables, has become an ubiquitous technique to improve convergence properties, simplify the…”
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DU-Shapley: A Shapley Value Proxy for Efficient Dataset Valuation by Garrido-Lucero, Felipe, Heymann, Benjamin, Vono, Maxime, Loiseau, Patrick, Perchet, Vianney

“…We consider the dataset valuation problem, that is, the problem of quantifying the incremental gain, to some relevant pre-defined utility of a machine learning…”
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DG-LMC: A Turn-key and Scalable Synchronous Distributed MCMC Algorithm via Langevin Monte Carlo within Gibbs by Plassier, Vincent, Vono, Maxime, Durmus, Alain, Moulines, Eric

“…Performing reliable Bayesian inference on a big data scale is becoming a keystone in the modern era of machine learning. A workhorse class of methods to…”
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QLSD: Quantised Langevin stochastic dynamics for Bayesian federated learning by Vono, Maxime, Plassier, Vincent, Durmus, Alain, Dieuleveut, Aymeric, Moulines, Eric

“…The objective of Federated Learning (FL) is to perform statistical inference for data which are decentralised and stored locally on networked clients. FL…”
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Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting by Vono, Maxime, Paulin, Daniel, Doucet, Arnaud

“…Performing exact Bayesian inference for complex models is computationally intractable. Markov chain Monte Carlo (MCMC) algorithms can provide reliable…”
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Split-and-augmented Gibbs sampler - Application to large-scale inference problems by Vono, Maxime, Dobigeon, Nicolas, Chainais, Pierre

“…This paper derives two new optimization-driven Monte Carlo algorithms inspired from variable splitting and data augmentation. In particular, the formulation of…”
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Mixture of noises and sampling of non-log-concave posterior distributions by Palud, Pierre, Chainais, Pierre, Petit, Franck Le, Bron, Emeric, Thouvenin, Pierre-Antoine, Vono, Maxime, Einig, L., Santa-Maria, M. Garcia, Gaudel, M., Orkisz, J. H., de Souza Magalhaes, V., Bardeau, S., Gerin, M., Goicoechea, J. R., Gratier, P., Guzman, V. V., Kainulainen, J., Levrier, F., Peretto, N., Pety, J., Roueff, A., Sievers, A.

“…This work considers a challenging radio-astronomy inverse problem of physical parameter inference from multispectral observations. The forward model underlying…”
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Gas kinematics around filamentary structures in the Orion B cloud by Gaudel, Mathilde, Orkisz, Jan H, Gerin, Maryvonne, Pety, Jérôme, Roueff, Antoine, Marchal, Antoine, Levrier, François, Miville-Deschênes, Marc-Antoine, Goicoechea, Javier R, Roueff, Evelyne, Petit, Franck Le, Magalhaes, Victor de Souza, Palud, Pierre, Santa-Maria, Miriam G, Vono, Maxime, Bardeau, Sébastien, Bron, Emeric, Chainais, Pierre, Chanussot, Jocelyn, Gratier, Pierre, Guzman, Viviana, Hughes, Annie, Kainulainen, Jouni, Languignon, David, Bourlot, Jacques Le, Liszt, Harvey, Öberg, Karin, Peretto, Nicolas, Sievers, Albrecht, Tremblin, Pascal

“…A&A 670, A59 (2023) Understanding the initial properties of star-forming material and how they affect the star formation process is key. From an observational…”
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Quantitative inference of the $H_2$ column densities from 3 mm molecular emission: A case study towards Orion B by Gratier, Pierre, Pety, Jérôme, Bron, Emeric, Roueff, Antoine, Orkisz, Jan H, Gerin, Maryvonne, Magalhaes, Victor de Souza, Gaudel, Mathilde, Vono, Maxime, Bardeau, Sébastien, Chanussot, Jocelyn, Chainais, Pierre, Goicoechea, Javier R, Guzmán, Viviana V, Hughes, Annie, Kainulainen, Jouni, Languignon, David, Bourlot, Jacques Le, Petit, Franck Le, Levrier, François, Liszt, Harvey, Peretto, Nicolas, Roueff, Evelyne, Sievers, Albrecht

“…A&A 645, A27 (2021) Molecular hydrogen being unobservable in cold molecular clouds, the column density measurements of molecular gas currently rely either on…”
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Tracers of the ionization fraction in dense and translucent gas: I. Automated exploitation of massive astrochemical model grids by Bron, Emeric, Roueff, Evelyne, Gerin, Maryvonne, Pety, Jérôme, Gratier, Pierre, Petit, Franck Le, Guzman, Viviana, Orkisz, Jan H, Magalhaes, Victor de Souza, Gaudel, Mathilde, Vono, Maxime, Bardeau, Sébastien, Chainais, Pierre, Goicoechea, Javier R, Hughes, Annie, Kainulainen, Jouni, Languignon, David, Bourlot, Jacques Le, Levrier, François, Liszt, Harvey, Öberg, Karin, Peretto, Nicolas, Roueff, Antoine, Sievers, Albrecht

“…A&A 645, A28 (2021) The ionization fraction plays a key role in the physics and chemistry of the neutral interstellar medium, from controlling the coupling of…”
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C18O, 13CO, and 12CO abundances and excitation temperatures in the Orion B molecular cloud: An analysis of the precision achievable when modeling spectral line within the Local Thermodynamic Equilibrium approximation by Roueff, Antoine, Gerin, Maryvonne, Gratier, Pierre, Levrier, Francois, Pety, Jerome, Gaudel, Mathilde, Goicoechea, Javier R, Orkisz, Jan H, Magalhaes, Victor de Souza, Vono, Maxime, Bardeau, Sebastien, Bron, Emeric, Chanussot, Jocelyn, Chainais, Pierre, Guzman, Viviana V, Hughes, Annie, Kainulainen, Jouni, Languignon, David, Bourlot, Jacques Le, Petit, Franck Le, Liszt, Harvey S, Marchal, Antoine, Miville-Deschenes, Marc-Antoine, Peretto, Nicolas, Roueff, Evelyne, Sievers, Albrecht

“…A&A 645, A26 (2021) CO isotopologue transitions are routinely observed in molecular clouds to probe the column density of the gas, the elemental ratios of…”
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