Samuel Vaiter

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All published works

Action	Title	Year	Authors
+	Bilevel gradient methods and Morse parametric qualification	2025	Jérôme Bolte Quoc-Tung Le Edouard Pauwels Samuel Vaiter
+ PDF Chat	Risk Estimate under a Nonstationary Autoregressive Model for Data-Driven Reproduction Number Estimation	2024	Barbara Pascal Samuel Vaiter
+ PDF Chat	Geometric and computational hardness of bilevel programming	2024	Jérôme Bolte Quoc-Tung Le Edouard Pauwels Samuel Vaiter
+ PDF Chat	CHANI: Correlation-based Hawkes Aggregation of Neurons with bio-Inspiration	2024	Sophie Jaffard Samuel Vaiter Patricia Reynaud-Bouret
+ PDF Chat	Derivatives of Stochastic Gradient Descent	2024	Franck Iutzeler Edouard Pauwels Samuel Vaiter
+	A theory of optimal convex regularization for low-dimensional recovery	2024	Yann Traonmilin Rémi Gribonval Samuel Vaiter
+ PDF Chat	The Derivatives of Sinkhorn–Knopp Converge	2023	Edouard Pauwels Samuel Vaiter
+ PDF Chat	The Geometry of Sparse Analysis Regularization	2023	Xavier Dupuis Samuel Vaiter
+ PDF Chat	Convergence of Message Passing Graph Neural Networks with Generic Aggregation On Random Graphs	2023	Matthieu Cordonnier Nicolas Keriven Nicolas Tremblay Samuel Vaiter
+ PDF Chat	Convergence of Message Passing Graph Neural Networks with Generic Aggregation On Large Random Graphs	2023	Matthieu Cordonnier Nicolas Keriven Nicolas Tremblay Samuel Vaiter
+	Local linear convergence of proximal coordinate descent algorithm	2023	Quentin Klopfenstein Quentin Bertrand Alexandre Gramfort Joseph Salmon Samuel Vaiter
+ PDF Chat	Supervised Learning of Analysis-Sparsity Priors With Automatic Differentiation	2023	Hashem Ghanem Joseph Salmon Nicolas Keriven Samuel Vaiter
+	A Lower Bound and a Near-Optimal Algorithm for Bilevel Empirical Risk Minimization	2023	Mathieu Dagréou Thomas Moreau Samuel Vaiter Pierre Ablin
+	On the Robustness of Text Vectorizers	2023	Rémi Catellier Samuel Vaiter Damien Garreau
+	Gradient scarcity with Bilevel Optimization for Graph Learning	2023	Hashem Ghanem Samuel Vaiter Nicolas Keriven
+	Provable local learning rule by expert aggregation for a Hawkes network	2023	Sophie Jaffard Samuel Vaiter Alexandre Muzy Patricia Reynaud-Bouret
+	Convergence of Message Passing Graph Neural Networks with Generic Aggregation On Large Random Graphs	2023	Matthieu Cordonnier Nicolas Keriven Nicolas Tremblay Samuel Vaiter
+	One-step differentiation of iterative algorithms	2023	Jérôme Bolte Edouard Pauwels Samuel Vaiter
+	What functions can Graph Neural Networks compute on random graphs? The role of Positional Encoding	2023	Nicolas Keriven Samuel Vaiter
+ PDF Chat	Benchopt: Reproducible, efficient and collaborative optimization benchmarks	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
+ PDF Chat	The derivatives of Sinkhorn-Knopp converge	2022	Edouard Pauwels Samuel Vaiter
+ PDF Chat	A framework for bilevel optimization that enables stochastic and global variance reduction algorithms	2022	Mathieu Dagréou Pierre Ablin Samuel Vaiter Thomas Moreau
+ PDF Chat	Sparse and smooth: Improved guarantees for spectral clustering in the dynamic stochastic block model	2022	Nicolas Keriven Samuel Vaiter
+	Automatic differentiation of nonsmooth iterative algorithms	2022	Jérôme Bolte Edouard Pauwels Samuel Vaiter
+	Benchopt: Reproducible, efficient and collaborative optimization benchmarks	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
+	A framework for bilevel optimization that enables stochastic and global variance reduction algorithms	2022	Mathieu Dagréou Pierre Ablin Samuel Vaiter Thomas Moreau
+	The derivatives of Sinkhorn-Knopp converge	2022	Edouard Pauwels Samuel Vaiter
+ PDF Chat	Linear support vector regression with linear constraints	2021	Quentin Klopfenstein Samuel Vaiter
+ PDF Chat	Automated Data-Driven Selection of the Hyperparameters for Total-Variation-Based Texture Segmentation	2021	Barbara Pascal Samuel Vaiter Nelly Pustelnik Patrice Abry
+ PDF Chat	Implicit differentiation for fast hyperparameter selection in non-smooth convex learning	2021	Quentin Bertrand Quentin Klopfenstein Mathurin Massias Mathieu Blondel Samuel Vaiter Alexandre Gramfort Joseph Salmon
+	From optimization to algorithmic differentiation: a graph detour	2021	Samuel Vaiter
+	A theory of optimal convex regularization for low-dimensional recovery	2021	Yann Traonmilin Rémi Gribonval Samuel Vaiter
+	On the Universality of Graph Neural Networks on Large Random Graphs	2021	Nicolas Keriven Alberto Bietti Samuel Vaiter
+	Supervised learning of analysis-sparsity priors with automatic differentiation	2021	Hashem Ghanem Joseph Salmon Nicolas Keriven Samuel Vaiter
+	Implicit differentiation for fast hyperparameter selection in non-smooth convex learning	2021	Quentin Bertrand Quentin Klopfenstein Mathurin Massias Mathieu Blondel Samuel Vaiter Alexandre Gramfort Joseph Salmon
+ PDF Chat	Convergence and Stability of Graph Convolutional Networks on Large Random Graphs	2020	Nicolas Keriven Alberto Bietti Samuel Vaiter
+ PDF Chat	Block-Based Refitting in $$\ell _{12}$$ Sparse Regularization	2020	Charles‐Alban Deledalle Nicolas Papadakis Joseph Salmon Samuel Vaiter
+ PDF Chat	Dual Extrapolation for Sparse GLMs	2020	Mathurin Massias Samuel Vaiter Alexandre Gramfort Joseph Salmon
+	Automated data-driven selection of the hyperparameters for Total-Variation based texture segmentation	2020	Barbara Pascal Samuel Vaiter Nelly Pustelnik Patrice Abry
+	Implicit differentiation of Lasso-type models for hyperparameter optimization	2020	Quentin Bertrand Quentin Klopfenstein Mathieu Blondel Samuel Vaiter Alexandre Gramfort Joseph Salmon
+	Model identification and local linear convergence of coordinate descent	2020	Quentin Klopfenstein Quentin Bertrand Alexandre Gramfort Joseph Salmon Samuel Vaiter
+	Automated data-driven selection of the hyperparameters for Total-Variation based texture segmentation	2020	Barbara Pascal Samuel Vaiter Nelly Pustelnik Patrice Abry
+	Convergence and Stability of Graph Convolutional Networks on Large Random Graphs	2020	Nicolas Keriven Alberto Bietti Samuel Vaiter
+	Sparse and Smooth: improved guarantees for Spectral Clustering in the Dynamic Stochastic Block Model	2020	Nicolas Keriven Samuel Vaiter
+	Block based refitting in $\ell_{12}$ sparse regularisation	2019	Charles‐Alban Deledalle Nicolas Papadakis Joseph Salmon Samuel Vaiter
+ PDF Chat	Exploiting regularity in sparse Generalized Linear Models	2019	Mathurin Massias Samuel Vaiter Alexandre Gramfort Joseph Salmon
+ PDF Chat	Refitting solutions promoted by $\ell_{12}$ sparse analysis regularization with block penalties	2019	Charles‐Alban Deledalle Nicolas Papadakis Joseph Salmon Samuel Vaiter
+	Refitting Solutions Promoted by $$\ell _{12}$$ Sparse Analysis Regularizations with Block Penalties	2019	Charles‐Alban Deledalle Nicolas Papadakis Joseph Salmon Samuel Vaiter
+	Dual Extrapolation for Sparse Generalized Linear Models	2019	Mathurin Massias Samuel Vaiter Alexandre Gramfort Joseph Salmon
+	Block based refitting in $\ell_{12}$ sparse regularisation	2019	Charles‐Alban Deledalle Nicolas Papadakis Joseph Salmon Samuel Vaiter
+	Refitting solutions promoted by $\ell_{12}$ sparse analysis regularization with block penalties	2019	Charles‐Alban Deledalle Nicolas Papadakis Joseph Salmon Samuel Vaiter
+	Optimality of 1-norm regularization among weighted 1-norms for sparse recovery: a case study on how to find optimal regularizations	2018	Yann Traonmilin Samuel Vaiter
+ PDF Chat	Maximal Solutions of Sparse Analysis Regularization	2018	Abdessamad Barbara A. Jourani Samuel Vaiter
+	Is the 1-norm the best convex sparse regularization?	2018	Yann Traonmilin Samuel Vaiter Rémi Gribonval
+	Recovery guarantees for low complexity models (Conference Presentation)	2017	Samuel Vaiter Gabriel Peyré Jalal Fadili
+	A sharp oracle inequality for Graph-Slope	2017	Pierre Bellec Joseph Salmon Samuel Vaiter
+ PDF Chat	Model Consistency of Partly Smooth Regularizers	2017	Samuel Vaiter Gabriel Peyré Jalal Fadili
+ PDF Chat	Accelerated Alternating Descent Methods for Dykstra-Like Problems	2017	Antonin Chambolle Pauline Tan Samuel Vaiter
+	Maximal Solutions of Sparse Analysis Regularization	2017	Abdessamad Barbara Abderrahim Jourani Samuel Vaiter
+ PDF Chat	CLEAR: Covariant LEAst-Square Refitting with Applications to Image Restoration	2017	Charles‐Alban Deledalle Nicolas Papadakis Joseph Salmon Samuel Vaiter
+	A sharp oracle inequality for Graph-Slope	2017	Pierre Bellec Joseph Salmon Samuel Vaiter
+	Maximal Solutions of Sparse Analysis Regularization	2017	Abdessamad Barbara Abderrahim Jourani Samuel Vaiter
+	A sharp oracle inequality for Graph-Slope	2017	Pierre Bellec Joseph Salmon Samuel Vaiter
+	CLEAR: Covariant LEAst-square Re-fitting with applications to image restoration	2016	C-A. Deledalle Nicolas Papadakis Joseph Salmon Samuel Vaiter
+ PDF Chat	The degrees of freedom of partly smooth regularizers	2016	Samuel Vaiter Charles Deledalle Jalal Fadili Gabriel Peyré Charles H Dossal
+	Proceedings of the third "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'16)	2016	Laurent Jacques Christophe De Vleeschouwer Y. Boursier Prasad Sudhakar Christine De Mol Aleksandra Pižurica Sandrine Anthoine Pierre Vandergheynst Pascal Frossard Çağdaş Bilen
+	Characterizing the maximum parameter of the total-variation denoising through the pseudo-inverse of the divergence	2016	Charles‐Alban Deledalle Nicolas Papadakis Joseph Salmon Samuel Vaiter
+	CLEAR: Covariant LEAst-square Re-fitting with applications to image restoration	2016	Charles‐Alban Deledalle Nicolas Papadakis Joseph Salmon Samuel Vaiter
+	Model selection with low complexity priors	2015	Samuel Vaiter Mohammad Golbabaee Jalal Fadili Gabriel Peyré
+ PDF Chat	Low Complexity Regularization of Linear Inverse Problems	2015	Samuel Vaiter Gabriel Peyré Jalal Fadili
+ PDF Chat	Sampling Theory, a Renaissance	2015	Samuel Vaiter Gabriel Peyré Jalal Fadili
+ PDF Chat	Model Selection with Low Complexity Priors	2015	Samuel Vaiter Mohammad Golbabaee Jalal Fadili Gabriel Peyré
+	Régularisations de faible complexité pour les problèmes inverses	2014	Samuel Vaiter
+ PDF Chat	Low Complexity Regularizations of Inverse Problems	2014	Samuel Vaiter
+ PDF Chat	Low Complexity Regularization of Inverse Problems	2014	Samuel Vaiter
+	Stein Unbiased GrAdient estimator of the Risk (SUGAR) for multiple parameter selection	2014	Charles‐Alban Deledalle Samuel Vaiter Jalal Fadili Gabriel Peyré
+	Partly Smooth Regularization of Inverse Problems	2014	Samuel Vaiter Gabriel Peyré Jalal Fadili
+	The Degrees of Freedom of Partly Smooth Regularizers	2014	Samuel Vaiter Charles‐Alban Deledalle Jalal Fadili Gabriel Peyré Charles Dossal
+ PDF Chat	Stein Unbiased GrAdient estimator of the Risk (SUGAR) for Multiple Parameter Selection	2014	Charles‐Alban Deledalle Samuel Vaiter Jalal Fadili Gabriel Peyré
+	Stein Unbiased GrAdient estimator of the Risk (SUGAR) for multiple parameter selection	2014	Charles‐Alban Deledalle Samuel Vaiter Jalal Fadili Gabriel Peyré
+	The Degrees of Freedom of Partly Smooth Regularizers	2014	Samuel Vaiter Charles‐Alban Deledalle Jalal Fadili Gabriel Peyré Charles Dossal
+	Low Complexity Regularization of Linear Inverse Problems	2014	Samuel Vaiter Gabriel Peyré Jalal Fadili
+ PDF Chat	Reconstruction Stable par Régularisation Décomposable Analyse	2013	Jalal Fadili Gabriel Peyré Samuel Vaiter Charles‐Alban Deledalle Joseph Salmon
+ PDF Chat	Robustesse au bruit des régularisations polyhédrales	2013	Samuel Vaiter Gabriel Peyré Jalal Fadili
+	Model Selection with Low Complexity Priors	2013	Samuel Vaiter Mohammad Golbabaee Jalal Fadili Gabriel Peyré
+	Model Selection with Piecewise Regular Gauges	2013	Samuel Vaiter Mohammad Golbabaee Jalal Fadili Gabriel Peyré
+ PDF Chat	Robust Polyhedral Regularization	2013	Samuel Vaiter Gabriel Peyré Jalal Fadili
+	Stable Recovery with Analysis Decomposable Priors	2013	M.J. Fadili Gabriel Peyré Samuel Vaiter Charles‐Alban Deledalle Joseph Salmon
+ PDF Chat	Robust Polyhedral Regularization	2013	Samuel Vaiter Gabriel Peyré Jalal Fadili
+	Robust Polyhedral Regularization	2013	Samuel Vaiter Gabriel Peyré Jalal Fadili
+	Robust Polyhedral Regularization	2013	Samuel Vaiter Gabriel Peyré Jalal Fadili
+ PDF Chat	Robust Sparse Analysis Regularization	2012	Samuel Vaiter Gabriel Peyré Charles H Dossal Jalal Fadili
+	Local behavior of sparse analysis regularization: Applications to risk estimation	2012	Samuel Vaiter Charles-Alban Deledalle Gabriel Peyré Charles Dossal Jalal Fadili
+ PDF Chat	Proximal Splitting Derivatives for Risk Estimation	2012	Charles‐Alban Deledalle Samuel Vaiter Gabriel Peyré Jalal Fadili Ch. Dossal
+ PDF Chat	Unbiased risk estimation for sparse analysis regularization	2012	Charles‐Alban Deledalle Samuel Vaiter Gabriel Peyré Jalal Fadili Charles Dossal
+ PDF Chat	The Degrees of Freedom of the Group Lasso	2012	Samuel Vaiter Charles Deledalle Gabriel Peyré Jalal Fadili Charles Dossal
+	The degrees of freedom of the Group Lasso for a General Design	2012	Samuel Vaiter Charles Deledalle Gabriel Peyré Jalal Fadili Charles Dossal
+	Risk estimation for matrix recovery with spectral regularization	2012	Charles‐Alban Deledalle Samuel Vaiter Gabriel Peyré Jalal Fadili Charles Dossal
+	The Degrees of Freedom of the Group Lasso	2012	Samuel Vaiter Charles‐Alban Deledalle Gabriel Peyré Jalal Fadili Charles Dossal
+ PDF Chat	The Degrees of Freedom of the Group Lasso	2012	Samuel Vaiter Charles Deledalle Gabriel Peyré Jalal Fadili Charles Dossal
+	Robust Sparse Analysis Regularization	2011	Samuel Vaiter Gabriel Peyré Charles Dossal Jalal Fadili
+	Robust Sparse Analysis Regularization	2011	Samuel Vaiter Gabriel Peyré Charles Dossal Jalal Fadili

Common Coauthors

Coauthor	Papers Together
Gabriel Peyré	35
Jalal Fadili	31
Joseph Salmon	27
Charles‐Alban Deledalle	20
Nicolas Keriven	12
Charles Dossal	11
Nicolas Papadakis	10
Alexandre Gramfort	10
Quentin Klopfenstein	7
Mathurin Massias	6
Mohammad Golbabaee	5
Edouard Pauwels	5
Quentin Bertrand	5
Thomas Moreau	5
Mathieu Dagréou	5
Pierre Ablin	5
Charles Deledalle	4
Barbara Pascal	4
Jérôme Bolte	4
Yann Traonmilin	4
Rémi Gribonval	4
Nicolas Tremblay	3
Jalal Fadili	3
Alberto Bietti	3
Abderrahim Jourani	3
Abdessamad Barbara	3
Matthieu Cordonnier	3
Nelly Pustelnik	3
Pierre Bellec	3
Edouard Pauwels	3
Patrice Abry	3
Hashem Ghanem	3
Mathieu Blondel	3
Pierre‐Antoine Bannier	2
Cássio F. Dantas	2
Charles H Dossal	2
Quoc-Tung Le	2
Badr Moufad	2
En Lai	2
Ghislain Durif	2
Tanguy Lefort	2
Sophie Jaffard	2
Tom Dupré la Tour	2
Benjamin Charlier	2
Benoit Malézieux	2
Johan Larsson	2
Alain Rakotomamonjy	2
Zaccharie Ramzi	2
Patricia Reynaud-Bouret	2
Nicolas Dobigeon	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Regression Shrinkage and Selection Via the Lasso	1996	Robert Tibshirani	27
+ PDF Chat	A First-Order Primal-Dual Algorithm for Convex Problems with Applications to Imaging	2010	Antonin Chambolle Thomas Pock	21
+ PDF Chat	Robust Sparse Analysis Regularization	2012	Samuel Vaiter Gabriel Peyré Charles H Dossal Jalal Fadili	18
+ PDF Chat	Model Selection and Estimation in Regression with Grouped Variables	2005	Ming Yuan Yi Lin	17
+ PDF Chat	Estimation of the Mean of a Multivariate Normal Distribution	1981	Charles Stein	15
+ PDF Chat	Sparsity and Smoothness Via the Fused Lasso	2004	Robert Tibshirani Michael A. Saunders Saharon Rosset Ji Zhu Keith Knight	14
+	Local behavior of sparse analysis regularization: Applications to risk estimation	2012	Samuel Vaiter Charles-Alban Deledalle Gabriel Peyré Charles Dossal Jalal Fadili	13
+	Linear convergence rates for Tikhonov regularization with positively homogeneous functionals	2011	Markus Grasmair	12
+ PDF Chat	The cosparse analysis model and algorithms	2012	Sangwook Nam Mike E. Davies Michael Elad Rémi Gribonval	12
+ PDF Chat	Model Consistency of Partly Smooth Regularizers	2017	Samuel Vaiter Gabriel Peyré Jalal Fadili	12
+ PDF Chat	On the “degrees of freedom” of the lasso	2007	Hui Zou Trevor Hastie Robert Tibshirani	11
+	Consistency of the group Lasso and multiple kernel learning	2007	Francis Bach	11
+	Degrees of freedom in lasso problems	2012	Ryan J. Tibshirani Jonathan Taylor	10
+	How Biased is the Apparent Error Rate of a Prediction Rule?	1986	Bradley Efron	10
+ PDF Chat	The Convex Geometry of Linear Inverse Problems	2012	Venkat Chandrasekaran Benjamin Recht Pablo A. Parrilo Alan S. Willsky	10
+	Active Sets, Nonsmoothness, and Sensitivity	2002	Adrian S. Lewis	10
+ PDF Chat	The solution path of the generalized lasso	2011	Ryan J. Tibshirani Jonathan Taylor	10
+ PDF Chat	Generalized SURE for Exponential Families: Applications to Regularization	2008	Yonina C. Eldar	9
+ PDF Chat	On the Equivalence of Soft Wavelet Shrinkage, Total Variation Diffusion, Total Variation Regularization, and SIDEs	2004	Gabriele Steidl Joachim Weickert Thomas Brox Pavel Mrázek Martin Welk	9
+	A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems	2009	Amir Beck Marc Teboulle	9
+ PDF Chat	Simple bounds for recovering low-complexity models	2012	Emmanuel J. Candès Benjamin Recht	9
+	Convergence rates of convex variational regularization	2004	Martin Burger Stanley Osher	8
+ PDF Chat	Least angle regression	2004	Bradley Efron Trevor Hastie Iain M. Johnstone Robert Tibshirani	8
+	Convex Analysis and Monotone Operator Theory in Hilbert Spaces	2017	Heinz H. Bauschke Patrick L. Combettes	8
+	Signal Recovery by Proximal Forward-Backward Splitting	2005	Patrick L. Combettes Valérie R. Wajs	8
+	Uncertainty principles and ideal atomic decomposition	2001	David L. Donoho Xiaoming Huo	8
+	On the degrees of freedom in shrinkage estimation	2008	Kengo Kato	8
+ PDF Chat	A SURE Approach for Digital Signal/Image Deconvolution Problems	2009	Jean‐Christophe Pesquet Amel Benazza-Benyahia Caroline Chaux	8
+ PDF Chat	Anti-sparse coding for approximate nearest neighbor search	2012	Hervé Jeǵou Teddy Furon Jean–Jacques Fuchs	8
+	Threshold selection for group sparsity	2010	Victor Solo Magnús Ö. Úlfarsson	7
+ PDF Chat	Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization	2010	Benjamin Recht Maryam Fazel Pablo A. Parrilo	7
+ PDF Chat	The degrees of freedom of the Lasso for general design matrix	2012	Charles H Dossal Maher Kachour M.J. Fadili Gabriel Peyré Christophe Chesneau	7
+	Identifying active constraints via partial smoothness and prox-regularity	2003	Warren Hare Adrian S. Lewis	7
+ PDF Chat	The degrees of freedom of partly smooth regularizers	2016	Samuel Vaiter Charles Deledalle Jalal Fadili Gabriel Peyré Charles H Dossal	7
+	Identifiable Surfaces in Constrained Optimization	1993	Stephen J. Wright	7
+	Generalized Cross-Validation as a Method for Choosing a Good Ridge Parameter	1979	Gene H. Golub Michael T. Heath Grace Wahba	7
+ PDF Chat	Proximal Splitting Methods in Signal Processing	2011	Patrick L. Combettes Jean‐Christophe Pesquet	7
+	Partial Smoothness, Tilt Stability, and Generalized Hessians	2013	Adrian S. Lewis S. Zhang	7
+ PDF Chat	Simultaneously Structured Models With Application to Sparse and Low-Rank Matrices	2015	Samet Oymak Amin Jalali Maryam Fazel Yonina C. Eldar Babak Hassibi	7
+	Sparse Approximate Solutions to Linear Systems	1995	B. K. Natarajan	6
+	Identifying Active Manifolds in Regularization Problems	2011	Warren Hare	6
+	A Unified Framework for High-Dimensional Analysis of $M$-Estimators with Decomposable Regularizers	2012	Sahand Negahban Pradeep Ravikumar Martin J. Wainwright Bin Yu	6
+	The projected GSURE for automatic parameter tuning in iterative shrinkage methods	2010	Raja Giryes Michael Elad Yonina C. Eldar	6
+	Consistency of trace norm minimization	2007	Francis Bach	6
+	The lasso problem and uniqueness	2013	Ryan J. Tibshirani	6
+ PDF Chat	A Natural Identity for Exponential Families with Applications in Multiparameter Estimation	1978	Harold Hudson	6
+	Matching pursuits with time-frequency dictionaries	1993	Stéphane Mallat Zhifeng Zhang	6
+	A Bias-Variance Approach for the Nonlocal Means	2011	Vincent Duval Jean–François Aujol Yann Gousseau	6
+	Perturbation Analysis of Optimization Problems	2000	J. Frédéric Bonnans Alexander Shapiro	6
+ PDF Chat	Uncertainty Principles and Vector Quantization	2010	Yurii Lyubarskii Roman Vershynin	6