Yohann de Castro

38 papers A* 2Journal 34Unranked 1

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Generalization Bounds of Surrogate Policies for Combinatorial Optimization Problems. CoRR Pierre-Cyril Aubin-Frankowski, Yohann de Castro, Axel Parmentier, Alessandro Rudi
2024	J	`jnl`	Node Regression on Latent Position Random Graphs via Local Averaging. CoRR Martin Gjorgjevski, Nicolas Keriven, Simon Barthelmé, Yohann de Castro
2024	J	`jnl`	Second Maximum of a Gaussian Random Field and Exact (t-)Spacing test. CoRR Jean-Marc Azaïs, Federico Dalmao, Yohann de Castro
2023	J	`jnl`	Exact recovery of the support of piecewise constant images via total variation regularization. CoRR Yohann de Castro, Vincent Duval, Romain Petit
2023	J	`jnl`	Neural Networks beyond explainability: Selective inference for sequence motifs. Trans. Mach. Learn. Res. Antoine Villié, Philippe Veber, Yohann de Castro, Laurent Jacob
2023	J	`jnl`	Towards Off-the-Grid Algorithms for Total Variation Regularized Inverse Problems. J. Math. Imaging Vis. Yohann de Castro, Vincent Duval, Romain Petit
2022	J	`jnl`	Neural Networks beyond explainability: Selective inference for sequence motifs. CoRR Antoine Villié, Philippe Veber, Yohann de Castro, Laurent Jacob
2022	J	`jnl`	Random Geometric Graph: Some recent developments and perspectives. CoRR Quentin Duchemin, Yohann de Castro
2022	J	`jnl`	Three rates of convergence or separation via U-statistics in a dependent framework. J. Mach. Learn. Res. Quentin Duchemin, Yohann de Castro, Claire Lacour
2021	J	`jnl`	Dual optimal design and the Christoffel-Darboux polynomial. Optim. Lett. Yohann de Castro, Fabrice Gamboa, Didier Henrion, Jean-Bernard Lasserre
2021	J	`jnl`	Forecasting Nonnegative Time Series via Sliding Mask Method (SMM) and Latent Clustered Forecast (LCF). CoRR Yohann de Castro, Luca Mencarelli
2021	—	`conf`	Towards Off-the-grid Algorithms for Total Variation Regularized Inverse Problems. SSVM Yohann de Castro, Vincent Duval, Romain Petit
2021	J	`jnl`	Towards Off-the-grid Algorithms for Total Variation Regularized Inverse Problems. CoRR Yohann de Castro, Vincent Duval, Romain Petit
2020	J	`jnl`	Markov Random Geometric Graph (MRGG): A Growth Model for Temporal Dynamic Networks. CoRR Yohann de Castro, Quentin Duchemin
2019	J	`jnl`	Latent Distance Estimation for Random Geometric Graphs. CoRR Ernesto Araya Valdivia, Yohann de Castro
2019	A*	`conf`	Latent distance estimation for random geometric graphs. NeurIPS Ernesto Araya Valdivia, Yohann de Castro
2019	J	`jnl`	Multiple Testing and Variable Selection along Least Angle Regression's path. CoRR Jean-Marc Azaïs, Yohann de Castro
2019	J	`jnl`	Nonnegative Matrix Factorization with Side Information for Time Series Recovery and Prediction. IEEE Trans. Knowl. Data Eng. Jiali Mei, Yohann de Castro, Yannig Goude, Jean-Marc Azaïs, Georges Hébrail
2019	J	`jnl`	On Representer Theorems and Convex Regularization. SIAM J. Optim. Claire Boyer, Antonin Chambolle, Yohann de Castro, Vincent Duval, Frédéric de Gournay, Pierre Weiss
2019	J	`jnl`	Sparse Regularization for Mixture Problems. CoRR Yohann de Castro, Sébastien Gadat, Clément Marteau, Cathy Maugis-Rabusseau
2018	J	`jnl`	Convex Regularization and Representer Theorems. CoRR Claire Boyer, Antonin Chambolle, Yohann de Castro, Vincent Duval, Frédéric de Gournay, Pierre Weiss
2018	J	`jnl`	On Representer Theorems and Convex Regularization. CoRR Claire Boyer, Antonin Chambolle, Yohann de Castro, Vincent Duval, Frédéric de Gournay, Pierre Weiss
2017	J	`jnl`	Approximate Optimal Designs for Multivariate Polynomial Regression. CoRR Yohann de Castro, Fabrice Gamboa, Didier Henrion, Roxana Hess, Jean-Bernard Lasserre
2017	J	`jnl`	Consistent Estimation of the Filtering and Marginal Smoothing Distributions in Nonparametric Hidden Markov Models. IEEE Trans. Inf. Theory Yohann de Castro, Elisabeth Gassiat, Sylvain Le Corff
2017	J	`jnl`	Exact Solutions to Super Resolution on Semi-Algebraic Domains in Higher Dimensions. IEEE Trans. Inf. Theory Yohann de Castro, Fabrice Gamboa, Didier Henrion, Jean B. Lasserre
2017	A*	`conf`	Nonnegative Matrix Factorization for Time Series Recovery From a Few Temporal Aggregates. ICML Jiali Mei, Yohann de Castro, Yannig Goude, Georges Hébrail
2017	J	`jnl`	Reconstructing Undirected Graphs from Eigenspaces. J. Mach. Learn. Res. Yohann de Castro, Thibault Espinasse, Paul Rochet
2017	J	`jnl`	Testing Gaussian Process with Applications to Super-Resolution. CoRR Jean-Marc Azaïs, Yohann de Castro, Stéphane Mourareau
2016	—	`book`	(Non) convex losses and regularizations, some contributions in Statistics. (Pertes et régularisations (non) convexes, quelques contributions en Statistique). Yohann de Castro
2016	J	`jnl`	Adapting to unknown noise level in sparse deconvolution. CoRR Claire Boyer, Yohann de Castro, Joseph Salmon
2016	J	`jnl`	Minimax Adaptive Estimation of Nonparametric Hidden Markov Models. J. Mach. Learn. Res. Yohann de Castro, Elisabeth Gassiat, Claire Lacour
2016	J	`jnl`	Reconstructing undirected graphs from eigenspaces. CoRR Yohann de Castro, Thibault Espinasse, Paul Rochet
2016	J	`jnl`	Restricted Isometry Constants for Gaussian and Rademacher matrices. CoRR Sandrine Dallaporta, Yohann de Castro
2015	J	`jnl`	Exact solutions to Super Resolution on semi-algebraic domains in higher dimensions. CoRR Yohann de Castro, Fabrice Gamboa, Didier Henrion, Jean B. Lasserre
2014	J	`jnl`	Optimal Designs for Lasso and Dantzig Selector Using Expander Codes. IEEE Trans. Inf. Theory Yohann de Castro
2011	J	`jnl`	A Remark on the Lasso and the Dantzig Selector CoRR Yohann de Castro
2011	J	`jnl`	Exact Reconstruction using Support Pursuit CoRR Yohann de Castro, Fabrice Gamboa
2010	J	`jnl`	Optimal designs for Lasso and Dantzig selector using Expander Codes. CoRR Yohann de Castro