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Mathurin Massias
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2020 – today
- 2024
- [j2]Cesare Molinari, Mathurin Massias, Lorenzo Rosasco, Silvia Villa:
Iterative regularization for low complexity regularizers. Numerische Mathematik 156(2): 641-689 (2024) - [i13]Can Pouliquen, Mathurin Massias, Titouan Vayer:
Schur's Positive-Definite Network: Deep Learning in the SPD cone with structure. CoRR abs/2406.09023 (2024) - 2023
- [c11]Johan Larsson, Quentin Klopfenstein, Mathurin Massias, Jonas Wallin:
Coordinate Descent for SLOPE. AISTATS 2023: 4802-4821 - [i12]Can Pouliquen, Paulo Gonçalves, Mathurin Massias, Titouan Vayer:
Implicit Differentiation for Hyperparameter Tuning the Weighted Graphical Lasso. CoRR abs/2307.02130 (2023) - 2022
- [j1]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: 149:1-149:43 (2022) - [c10]Boris Muzellec, Kanji Sato, Mathurin Massias, Taiji Suzuki:
Dimension-free convergence rates for gradient Langevin dynamics in RKHS. COLT 2022: 1356-1420 - [c9]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 - [c8]Quentin Bertrand, Quentin Klopfenstein, Pierre-Antoine Bannier, Gauthier Gidel, Mathurin Massias:
Beyond L1: Faster and Better Sparse Models with skglm. NeurIPS 2022 - [i11]Quentin Bertrand, Quentin Klopfenstein, Pierre-Antoine Bannier, Gauthier Gidel, Mathurin Massias:
Beyond L1: Faster and Better Sparse Models with skglm. CoRR abs/2204.07826 (2022) - [i10]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
Benchopt: Reproducible, efficient and collaborative optimization benchmarks. CoRR abs/2206.13424 (2022) - 2021
- [c7]Quentin Bertrand, Mathurin Massias:
Anderson acceleration of coordinate descent. AISTATS 2021: 1288-1296 - [c6]Cesare Molinari, Mathurin Massias, Lorenzo Rosasco, Silvia Villa:
Iterative regularization for convex regularizers. AISTATS 2021: 1684-1692 - [i9]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 abs/2105.01637 (2021) - 2020
- [c5]Mathurin Massias, Quentin Bertrand, Alexandre Gramfort, Joseph Salmon:
Support recovery and sup-norm convergence rates for sparse pivotal estimation. AISTATS 2020: 2655-2665 - [i8]Mathurin Massias, Quentin Bertrand, Alexandre Gramfort, Joseph Salmon:
Support recovery and sup-norm convergence rates for sparse pivotal estimation. CoRR abs/2001.05401 (2020) - [i7]Boris Muzellec, Kanji Sato, Mathurin Massias, Taiji Suzuki:
Dimension-free convergence rates for gradient Langevin dynamics in RKHS. CoRR abs/2003.00306 (2020) - [i6]Cesare Molinari, Mathurin Massias, Lorenzo Rosasco, Silvia Villa:
Implicit regularization for convex regularizers. CoRR abs/2006.09859 (2020) - [i5]Quentin Bertrand, Mathurin Massias:
Anderson acceleration of coordinate descent. CoRR abs/2011.10065 (2020)
2010 – 2019
- 2019
- [c4]Quentin Bertrand, Mathurin Massias, Alexandre Gramfort, Joseph Salmon:
Handling correlated and repeated measurements with the smoothed multivariate square-root Lasso. NeurIPS 2019: 3961-3972 - [c3]Pierre Ablin, Thomas Moreau, Mathurin Massias, Alexandre Gramfort:
Learning step sizes for unfolded sparse coding. NeurIPS 2019: 13100-13110 - [i4]Quentin Bertrand, Mathurin Massias, Alexandre Gramfort, Joseph Salmon:
Concomitant Lasso with Repetitions (CLaR): beyond averaging multiple realizations of heteroscedastic noise. CoRR abs/1902.02509 (2019) - [i3]Pierre Ablin, Thomas Moreau
Learning step sizes for unfolded sparse coding. CoRR abs/1905.11071 (2019) - [i2]Mathurin Massias, Samuel Vaiter, Alexandre Gramfort, Joseph Salmon:
Dual Extrapolation for Sparse Generalized Linear Models. CoRR abs/1907.05830 (2019) - 2018
- [c2]Mathurin Massias, Olivier Fercoq, Alexandre Gramfort, Joseph Salmon:
Generalized Concomitant Multi-Task Lasso for Sparse Multimodal Regression. AISTATS 2018: 998-1007 - [c1]Mathurin Massias, Joseph Salmon, Alexandre Gramfort:
Celer: a Fast Solver for the Lasso with Dual Extrapolation. ICML 2018: 3321-3330 - 2017
- [i1]Mathurin Massias, Alexandre Gramfort, Joseph Salmon:
From safe screening rules to working sets for faster Lasso-type solvers. CoRR abs/1703.07285 (2017)
Coauthor Index
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