Joseph Salmon

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 61

Top Topics

Provably Convergent

Top Venues

Publications

Tanguy Lefort, Antoine Affouard, Benjamin Charlier, Jean-Christophe Lombardo, Mathias Chouet, Hervé Goëau, Joseph Salmon, Pierre Bonnet, Alexis Joly
Cooperative learning of Pl@ntNet's Artificial Intelligence algorithm: how does it work and how can we improve it? CoRR (2024)
Tanguy Lefort, Benjamin Charlier, Alexis Joly, Joseph Salmon
Identify Ambiguous Tasks Combining Crowdsourced Labels by Weighting Areas Under the Margin. Trans. Mach. Learn. Res. 2024 (2024)
Quentin Klopfenstein, Quentin Bertrand, Alexandre Gramfort, Joseph Salmon, Samuel Vaiter
Local linear convergence of proximal coordinate descent algorithm. Optim. Lett. 18 (1) (2024)
Hashem Ghanem, Joseph Salmon, Nicolas Keriven, Samuel Vaiter
Supervised Learning of Analysis-Sparsity Priors With Automatic Differentiation. IEEE Signal Process. Lett. 30 (2023)
Paul Mangold, Aurélien Bellet, Joseph Salmon, Marc Tommasi
High-Dimensional Private Empirical Risk Minimization by Greedy Coordinate Descent. AISTATS (2023)
Camille Garcin, Maximilien Servajean, Alexis Joly, Joseph Salmon
A two-head loss function for deep Average-K classification. CoRR (2023)
Paul Mangold, Aurélien Bellet, Joseph Salmon, Marc Tommasi
Differentially Private Coordinate Descent for Composite Empirical Risk Minimization. ICML (2022)
Thomas Moreau, Mathurin Massias, Alexandre Gramfort, Pierre Ablin, Pierre-Antoine Bannier, Benjamin Charlier, Mathieu Dagréou, Tom Dupré la Tour, Ghislain Durif, Cássio F. Dantas, Quentin Klopfenstein, Johan Larsson, En Lai, Tanguy Lefort, Benoît Malézieux, Badr Moufad, Binh T. Nguyen, Alain Rakotomamonjy, Zaccharie Ramzi, Joseph Salmon, Samuel Vaiter
Benchopt: Reproducible, efficient and collaborative optimization benchmarks. CoRR (2022)
Tanguy Lefort, Benjamin Charlier, Alexis Joly, Joseph Salmon
Improve learning combining crowdsourced labels by weighting Areas Under the Margin. CoRR (2022)
Camille Garcin, Maximilien Servajean, Alexis Joly, Joseph Salmon
Stochastic smoothing of the top-K calibrated hinge loss for deep imbalanced classification. CoRR (2022)
Camille Garcin, Maximilien Servajean, Alexis Joly, Joseph Salmon
Stochastic smoothing of the top-K calibrated hinge loss for deep imbalanced classification. ICML (2022)
Quentin Bertrand, Quentin Klopfenstein, Mathurin Massias, Mathieu Blondel, Samuel Vaiter, Alexandre Gramfort, Joseph Salmon
Implicit Differentiation for Fast Hyperparameter Selection in Non-Smooth Convex Learning. J. Mach. Learn. Res. 23 (2022)
Kenan Sehic, Alexandre Gramfort, Joseph Salmon, Luigi Nardi
LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso. AutoML (2022)
Jérôme-Alexis Chevalier, Tuan-Binh Nguyen, Bertrand Thirion, Joseph Salmon
Spatially relaxed inference on high-dimensional linear models. Stat. Comput. 32 (5) (2022)
Alain Rakotomamonjy, Rémi Flamary, Joseph Salmon, Gilles Gasso
Convergent Working Set Algorithm for Lasso with Non-Convex Sparse Regularizers. AISTATS (2022)
Thomas Moreau, Mathurin Massias, Alexandre Gramfort, Pierre Ablin, Pierre-Antoine Bannier, Benjamin Charlier, Mathieu Dagréou, Tom Dupré la Tour, Ghislain Durif, Cássio F. Dantas, Quentin Klopfenstein, Johan Larsson, En Lai, Tanguy Lefort, Benoît Malézieux, Badr Moufad, Binh T. Nguyen, Alain Rakotomamonjy, Zaccharie Ramzi, Joseph Salmon, Samuel Vaiter
Benchopt: Reproducible, efficient and collaborative optimization benchmarks. NeurIPS (2022)
Paul Mangold, Aurélien Bellet, Joseph Salmon, Marc Tommasi
High-Dimensional Private Empirical Risk Minimization by Greedy Coordinate Descent. CoRR (2022)
Charles-Alban Deledalle, Nicolas Papadakis, Joseph Salmon, Samuel Vaiter
Sparse Regularization. J. Math. Imaging Vis. 63 (2) (2021)
Lang Liu, Joseph Salmon, Zaïd Harchaoui
Score-Based Change Detection For Gradient-Based Learning Machines. ICASSP (2021)
Paul Mangold, Aurélien Bellet, Joseph Salmon, Marc Tommasi
Differentially Private Coordinate Descent for Composite Empirical Risk Minimization. CoRR (2021)
Quentin Bertrand, Quentin Klopfenstein, Mathurin Massias, Mathieu Blondel, Samuel Vaiter, Alexandre Gramfort, Joseph Salmon
Implicit differentiation for fast hyperparameter selection in non-smooth convex learning. CoRR (2021)
Florent Bascou, Sophie Lèbre, Joseph Salmon
Elastic Net avec gestion des interactions et débiaisage. EGC (2021)
Camille Garcin, Alexis Joly, Pierre Bonnet, Antoine Affouard, Jean-Christophe Lombardo, Mathias Chouet, Maximilien Servajean, Titouan Lorieul, Joseph Salmon
Pl@ntNet-300K: a plant image dataset with high label ambiguity and a long-tailed distribution. NeurIPS Datasets and Benchmarks (2021)
Lang Liu, Joseph Salmon, Zaïd Harchaoui
Score-Based Change Detection for Gradient-Based Learning Machines. CoRR (2021)
Jérôme-Alexis Chevalier, Tuan-Binh Nguyen, Joseph Salmon, Gaël Varoquaux, Bertrand Thirion
Decoding with confidence: Statistical control on decoder maps. NeuroImage 234 (2021)
Kenan Sehic, Alexandre Gramfort, Joseph Salmon, Luigi Nardi
LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso. CoRR (2021)
Quentin Bertrand, Quentin Klopfenstein, Mathieu Blondel, Samuel Vaiter, Alexandre Gramfort, Joseph Salmon
Implicit differentiation of Lasso-type models for hyperparameter optimization. CoRR (2020)
Alain Rakotomamonjy, Rémi Flamary, Gilles Gasso, Joseph Salmon
Provably Convergent Working Set Algorithm for Non-Convex Regularized Regression. CoRR (2020)
Eugène Ndiaye, Olivier Fercoq, Joseph Salmon
Screening Rules and its Complexity for Active Set Identification. CoRR (2020)
Jérôme-Alexis Chevalier, Alexandre Gramfort, Joseph Salmon, Bertrand Thirion
Statistical control for spatio-temporal MEG/EEG source imaging with desparsified multi-task Lasso. CoRR (2020)
Quentin Bertrand, Quentin Klopfenstein, Mathieu Blondel, Samuel Vaiter, Alexandre Gramfort, Joseph Salmon
Implicit differentiation of Lasso-type models for hyperparameter optimization. ICML (2020)
Axel Parmentier, Victor Cohen, Vincent Leclère, Guillaume Obozinski, Joseph Salmon
Integer Programming on the Junction Tree Polytope for Influence Diagrams. INFORMS J. Optim. 2 (3) (2020)
Mathurin Massias, Quentin Bertrand, Alexandre Gramfort, Joseph Salmon
Support recovery and sup-norm convergence rates for sparse pivotal estimation. CoRR (2020)
Quentin Klopfenstein, Quentin Bertrand, Alexandre Gramfort, Joseph Salmon, Samuel Vaiter
Model identification and local linear convergence of coordinate descent. CoRR (2020)
Mathurin Massias, Quentin Bertrand, Alexandre Gramfort, Joseph Salmon
Support recovery and sup-norm convergence rates for sparse pivotal estimation. AISTATS (2020)
Jérôme-Alexis Chevalier, Joseph Salmon, Alexandre Gramfort, Bertrand Thirion
Statistical control for spatio-temporal MEG/EEG source imaging with desparsified mutli-task Lasso. NeurIPS (2020)
Charles-Alban Deledalle, Nicolas Papadakis, Joseph Salmon, Samuel Vaiter
Refitting Solutions Promoted by ℓ _12 Sparse Analysis Regularizations with Block Penalties. SSVM (2019)
Mathurin Massias, Samuel Vaiter, Alexandre Gramfort, Joseph Salmon
Dual Extrapolation for Sparse Generalized Linear Models. CoRR (2019)
Nidham Gazagnadou, Robert M. Gower, Joseph Salmon
Optimal mini-batch and step sizes for SAGA. CoRR (2019)
Quentin Bertrand, Mathurin Massias, Alexandre Gramfort, Joseph Salmon
Concomitant Lasso with Repetitions (CLaR): beyond averaging multiple realizations of heteroscedastic noise. CoRR (2019)
Alain Rakotomamonjy, Gilles Gasso, Joseph Salmon
Screening Rules for Lasso with Non-Convex Sparse Regularizers. CoRR (2019)
Nidham Gazagnadou, Robert M. Gower, Joseph Salmon
Optimal Mini-Batch and Step Sizes for SAGA. ICML (2019)
Eugène Ndiaye, Tam Le, Olivier Fercoq, Joseph Salmon, Ichiro Takeuchi
Safe Grid Search with Optimal Complexity. ICML (2019)
Alain Rakotomamonjy, Gilles Gasso, Joseph Salmon
Screening rules for Lasso with non-convex Sparse Regularizers. ICML (2019)
Quentin Bertrand, Mathurin Massias, Alexandre Gramfort, Joseph Salmon
Handling correlated and repeated measurements with the smoothed multivariate square-root Lasso. NeurIPS (2019)
Mathurin Massias, Joseph Salmon, Alexandre Gramfort
Celer: a Fast Solver for the Lasso with Dual Extrapolation. ICML (2018)
Jérôme-Alexis Chevalier, Joseph Salmon, Bertrand Thirion
Statistical Inference with Ensemble of Clustered Desparsified Lasso. MICCAI (1) (2018)
Eugène Ndiaye, Tam Le, Olivier Fercoq, Joseph Salmon, Ichiro Takeuchi
Safe Grid Search with Optimal Complexity. CoRR (2018)
Mathurin Massias, Olivier Fercoq, Alexandre Gramfort, Joseph Salmon
Generalized Concomitant Multi-Task Lasso for Sparse Multimodal Regression. AISTATS (2018)
Mathurin Massias, Alexandre Gramfort, Joseph Salmon
From safe screening rules to working sets for faster Lasso-type solvers. CoRR (2017)
Evgenii Chzhen, Christophe Denis, Mohamed Hebiri, Joseph Salmon
On the benefits of output sparsity for multi-label classification. CoRR (2017)
Eugène Ndiaye, Olivier Fercoq, Alexandre Gramfort, Joseph Salmon
Gap Safe Screening Rules for Sparsity Enforcing Penalties. J. Mach. Learn. Res. 18 (2017)
Charles-Alban Deledalle, Nicolas Papadakis, Joseph Salmon, Samuel Vaiter
CLEAR: Covariant LEAst-Square Refitting with Applications to Image Restoration. SIAM J. Imaging Sci. 10 (1) (2017)
Igor Colin, Aurélien Bellet, Joseph Salmon, Stéphan Clémençon
Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions. ICML (2016)
Igor Colin, Aurélien Bellet, Joseph Salmon, Stéphan Clémençon
Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions. CoRR (2016)
Eugène Ndiaye, Olivier Fercoq, Alexandre Gramfort, Joseph Salmon
GAP Safe Screening Rules for Sparse-Group Lasso. NIPS (2016)
Eugène Ndiaye, Olivier Fercoq, Alexandre Gramfort, Vincent Leclère, Joseph Salmon
Efficient Smoothed Concomitant Lasso Estimation for High Dimensional Regression. CoRR (2016)
Eugène Ndiaye, Olivier Fercoq, Alexandre Gramfort, Joseph Salmon
GAP Safe Screening Rules for Sparse-Group-Lasso. CoRR (2016)
Eugène Ndiaye, Olivier Fercoq, Alexandre Gramfort, Joseph Salmon
Gap Safe screening rules for sparsity enforcing penalties. CoRR (2016)
Claire Boyer, Yohann de Castro, Joseph Salmon
Adapting to unknown noise level in sparse deconvolution. CoRR (2016)
Charles-Alban Deledalle, Nicolas Papadakis, Joseph Salmon, Samuel Vaiter
CLEAR: Covariant LEAst-square Re-fitting with applications to image restoration. CoRR (2016)
Igor Colin, Aurélien Bellet, Joseph Salmon, Stéphan Clémençon
Extending Gossip Algorithms to Distributed Estimation of U-statistics. NIPS (2015)
Eugène Ndiaye, Olivier Fercoq, Alexandre Gramfort, Joseph Salmon
GAP Safe screening rules for sparse multi-task and multi-class models. CoRR (2015)
Eugène Ndiaye, Olivier Fercoq, Alexandre Gramfort, Joseph Salmon
GAP Safe screening rules for sparse multi-task and multi-class models. NIPS (2015)
Olivier Fercoq, Alexandre Gramfort, Joseph Salmon
Mind the duality gap: safer rules for the Lasso. CoRR (2015)
Olivier Fercoq, Alexandre Gramfort, Joseph Salmon
Mind the duality gap: safer rules for the Lasso. ICML (2015)
Igor Colin, Aurélien Bellet, Joseph Salmon, Stéphan Clémençon
Extending Gossip Algorithms to Distributed Estimation of U-Statistics. CoRR (2015)
Charles-Alban Deledalle, Nicolas Papadakis, Joseph Salmon
On Debiasing Restoration Algorithms: Applications to Total-Variation and Nonlocal-Means. SSVM (2015)
Jean Lafond, Olga Klopp, Eric Moulines, Joseph Salmon
Probabilistic low-rank matrix completion on finite alphabets. NIPS (2014)
David Günther, Joseph Salmon, Julien Tierny
Mandatory Critical Points of 2D Uncertain Scalar Fields. Comput. Graph. Forum 33 (3) (2014)
Joseph Salmon, Zachary T. Harmany, Charles-Alban Deledalle, Rebecca Willett
Poisson Noise Reduction with Non-local PCA. J. Math. Imaging Vis. 48 (2) (2014)
Arnak S. Dalalyan, Mohamed Hebiri, Katia Meziani, Joseph Salmon
Learning Heteroscedastic Models by Convex Programming under Group Sparsity. ICML (3) (2013)
Mohamed-Jalal Fadili, Gabriel Peyré, Samuel Vaiter, Charles-Alban Deledalle, Joseph Salmon
Stable Recovery with Analysis Decomposable Priors CoRR (2013)
Joseph Salmon, Yann Strozecki
Patch reprojections for Non-Local methods. Signal Process. 92 (2) (2012)
Joseph Salmon, Rebecca Willett, Ery Arias-Castro
A two-stage denoising filter: The preprocessed Yaroslavsky filter. SSP (2012)
Joseph Salmon, Zachary T. Harmany, Charles-Alban Deledalle, Rebecca Willett
Poisson noise reduction with non-local PCA CoRR (2012)
Joseph Salmon, Charles-Alban Deledalle, Rebecca Willett, Zachary T. Harmany
Poisson noise reduction with non-local PCA. ICASSP (2012)
Ery Arias-Castro, Joseph Salmon, Rebecca Willett
Oracle Inequalities and Minimax Rates for Nonlocal Means and Related Adaptive Kernel-Based Methods. SIAM J. Imaging Sci. 5 (3) (2012)
Charles-Alban Deledalle, Vincent Duval, Joseph Salmon
Non-local Methods with Shape-Adaptive Patches (NLM-SAP). J. Math. Imaging Vis. 43 (2) (2012)
Joseph Salmon, Rebecca Willett, Ery Arias-Castro
A two-stage denoising filter: the preprocessed Yaroslavsky filter CoRR (2012)
Joseph Salmon, Arnak S. Dalalyan
Optimal aggregation of affine estimators. COLT (2011)
Ery Arias-Castro, Joseph Salmon, Rebecca Willett
Oracle inequalities and minimax rates for non-local means and related adaptive kernel-based methods CoRR (2011)
Charles-Alban Deledalle, Joseph Salmon, Arnak S. Dalalyan
Image denoising with patch based PCA: local versus global. BMVC (2011)
Charles-Alban Deledalle, Vincent Duval, Joseph Salmon
Anisotropic Non-Local Means with Spatially Adaptive Patch Shapes. SSVM (2011)
Arnak S. Dalalyan, Joseph Salmon
Competing against the Best Nearest Neighbor Filter in Regression. ALT (2011)
Joseph Salmon
On Two Parameters for Denoising With Non-Local Means. IEEE Signal Process. Lett. 17 (3) (2010)
Joseph Salmon, Yann Strozecki
From patches to pixels in Non-Local methods: Weighted-average reprojection. ICIP (2010)
Joseph Salmon, Erwan Le Pennec
NL-Means and aggregation procedures. ICIP (2009)