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ORCIDYohann de Castro
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2020 – today
- 2024
[i21]Jean-Marc Azaïs, Federico Dalmao, Yohann de Castro:
Second Maximum of a Gaussian Random Field and Exact (t-)Spacing test. CoRR abs/2406.18397 (2024)- 2023
- [j11]Yohann de Castro
, Vincent Duval, Romain Petit:
Towards Off-the-Grid Algorithms for Total Variation Regularized Inverse Problems. J. Math. Imaging Vis. 65(1): 53-81 (2023) - [j10]Antoine Villié, Philippe Veber, Yohann de Castro, Laurent Jacob:
Neural Networks beyond explainability: Selective inference for sequence motifs. Trans. Mach. Learn. Res. 2023 (2023) - [i20]Yohann de Castro, Vincent Duval, Romain Petit:
Exact recovery of the support of piecewise constant images via total variation regularization. CoRR abs/2307.03709 (2023) - 2022
- [j9]Quentin Duchemin, Yohann de Castro, Claire Lacour:
Three rates of convergence or separation via U-statistics in a dependent framework. J. Mach. Learn. Res. 23: 201:1-201:59 (2022) - [i19]Quentin Duchemin, Yohann de Castro:
Random Geometric Graph: Some recent developments and perspectives. CoRR abs/2203.15351 (2022) - [i18]Antoine Villié, Philippe Veber, Yohann de Castro, Laurent Jacob:
Neural Networks beyond explainability: Selective inference for sequence motifs. CoRR abs/2212.12542 (2022) - 2021
- [j8]Yohann de Castro, Fabrice Gamboa, Didier Henrion, Jean-Bernard Lasserre:
Dual optimal design and the Christoffel-Darboux polynomial. Optim. Lett. 15(1): 3-8 (2021) - [c3]Yohann de Castro, Vincent Duval, Romain Petit:
Towards Off-the-grid Algorithms for Total Variation Regularized Inverse Problems. SSVM 2021: 553-564 - [i17]Yohann de Castro, Luca Mencarelli:
Forecasting Nonnegative Time Series via Sliding Mask Method (SMM) and Latent Clustered Forecast (LCF). CoRR abs/2102.05314 (2021) - [i16]Yohann de Castro, Vincent Duval, Romain Petit:
Towards Off-the-grid Algorithms for Total Variation Regularized Inverse Problems. CoRR abs/2104.06706 (2021) - 2020
- [i15]Yohann de Castro, Quentin Duchemin:
Markov Random Geometric Graph (MRGG): A Growth Model for Temporal Dynamic Networks. CoRR abs/2006.07001 (2020)
2010 – 2019
- 2019
- [j7]Claire Boyer, Antonin Chambolle, Yohann de Castro, Vincent Duval, Frédéric de Gournay, Pierre Weiss:
On Representer Theorems and Convex Regularization. SIAM J. Optim. 29(2): 1260-1281 (2019) - [j6]Jiali Mei, Yohann de Castro, Yannig Goude, Jean-Marc Azaïs, Georges Hébrail:
Nonnegative Matrix Factorization with Side Information for Time Series Recovery and Prediction. IEEE Trans. Knowl. Data Eng. 31(3): 493-506 (2019) - [c2]Ernesto Araya Valdivia, Yohann de Castro:
Latent distance estimation for random geometric graphs. NeurIPS 2019: 8721-8731 - [i14]Jean-Marc Azaïs, Yohann de Castro:
Multiple Testing and Variable Selection along Least Angle Regression's path. CoRR abs/1906.12072 (2019) - [i13]Yohann de Castro, Sébastien Gadat, Clément Marteau, Cathy Maugis-Rabusseau:
Sparse Regularization for Mixture Problems. CoRR abs/1907.10592 (2019) - [i12]Ernesto Araya Valdivia, Yohann de Castro:
Latent Distance Estimation for Random Geometric Graphs. CoRR abs/1909.06841 (2019) - 2018
- [i11]Claire Boyer, Antonin Chambolle, Yohann de Castro, Vincent Duval, Frédéric de Gournay, Pierre Weiss:
On Representer Theorems and Convex Regularization. CoRR abs/1806.09810 (2018) - [i10]Claire Boyer, Antonin Chambolle, Yohann de Castro, Vincent Duval, Frédéric de Gournay, Pierre Weiss:
Convex Regularization and Representer Theorems. CoRR abs/1812.04355 (2018) - 2017
- [j5]Yohann de Castro, Thibault Espinasse, Paul Rochet:
Reconstructing Undirected Graphs from Eigenspaces. J. Mach. Learn. Res. 18: 51:1-51:24 (2017) - [j4]Yohann de Castro, Fabrice Gamboa, Didier Henrion, Jean B. Lasserre:
Exact Solutions to Super Resolution on Semi-Algebraic Domains in Higher Dimensions. IEEE Trans. Inf. Theory 63(1): 621-630 (2017) - [j3]Yohann de Castro, Elisabeth Gassiat, Sylvain Le Corff:
Consistent Estimation of the Filtering and Marginal Smoothing Distributions in Nonparametric Hidden Markov Models. IEEE Trans. Inf. Theory 63(8): 4758-4777 (2017) - [c1]Jiali Mei, Yohann de Castro, Yannig Goude, Georges Hébrail:
Nonnegative Matrix Factorization for Time Series Recovery From a Few Temporal Aggregates. ICML 2017: 2382-2390 - [i9]Jean-Marc Azaïs, Yohann de Castro, Stéphane Mourareau:
Testing Gaussian Process with Applications to Super-Resolution. CoRR abs/1706.00679 (2017) - [i8]Yohann de Castro, Fabrice Gamboa, Didier Henrion, Roxana Hess, Jean-Bernard Lasserre:
Approximate Optimal Designs for Multivariate Polynomial Regression. CoRR abs/1706.04059 (2017) - 2016
- [b1]Yohann de Castro:
(Non) convex losses and regularizations, some contributions in Statistics. (Pertes et régularisations (non) convexes, quelques contributions en Statistique). University of Paris-Saclay, France, 2016 - [j2]Yohann de Castro, Elisabeth Gassiat, Claire Lacour:
Minimax Adaptive Estimation of Nonparametric Hidden Markov Models. J. Mach. Learn. Res. 17: 111:1-111:43 (2016) - [i7]Yohann de Castro, Thibault Espinasse, Paul Rochet:
Reconstructing undirected graphs from eigenspaces. CoRR abs/1603.08113 (2016) - [i6]Sandrine Dallaporta, Yohann de Castro:
Restricted Isometry Constants for Gaussian and Rademacher matrices. CoRR abs/1604.01171 (2016) - [i5]Claire Boyer, Yohann de Castro, Joseph Salmon:
Adapting to unknown noise level in sparse deconvolution. CoRR abs/1606.04760 (2016) - 2015
- [i4]Yohann de Castro, Fabrice Gamboa, Didier Henrion, Jean B. Lasserre:
Exact solutions to Super Resolution on semi-algebraic domains in higher dimensions. CoRR abs/1502.02436 (2015) - 2014
- [j1]Yohann de Castro:
Optimal Designs for Lasso and Dantzig Selector Using Expander Codes. IEEE Trans. Inf. Theory 60(11): 7293-7299 (2014) - 2011
- [i3]Yohann de Castro, Fabrice Gamboa:
Exact Reconstruction using Support Pursuit. CoRR abs/1103.4951 (2011) - [i2]Yohann de Castro:
A Remark on the Lasso and the Dantzig Selector. CoRR abs/1108.5533 (2011) - 2010
- [i1]Yohann de Castro:
Optimal designs for Lasso and Dantzig selector using Expander Codes. CoRR abs/1010.2457 (2010)
Coauthor Index
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