scientific article; zbMATH DE number 7306926
From MaRDI portal
Publication:5149046
Sara van de Geer, Francesco Ortelli
Publication date: 5 February 2021
Full work available at URL: https://arxiv.org/abs/1911.07231
Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Related Items
A cross-validation framework for signal denoising with applications to trend filtering, dyadic CART and beyond, Multivariate extensions of isotonic regression and total variation denoising via entire monotonicity and Hardy-Krause variation, Prediction bounds for higher order total variation regularized least squares, Tensor denoising with trend filtering
Cites Work
- Unnamed Item
- Unnamed Item
- Nonlinear total variation based noise removal algorithms
- Estimation and testing under sparsity. École d'Été de Probabilités de Saint-Flour XLV -- 2015
- Simple bounds for recovering low-complexity models
- On the prediction performance of the Lasso
- Oracle inequalities and optimal inference under group sparsity
- Locally adaptive regression splines
- Image recovery via total variation minimization and related problems
- Image denoising: Pointwise adaptive approach
- A sharp oracle inequality for graph-slope
- The Shannon total variation
- On the total variation regularized estimator over a class of tree graphs
- Sharp oracle inequalities for least squares estimators in shape restricted regression
- Adaptive estimation of a quadratic functional by model selection.
- Asymptotical minimax recovery of sets with smooth boundaries
- Sharp oracle inequalities for aggregation of affine estimators
- On the conditions used to prove oracle results for the Lasso
- Slope meets Lasso: improved oracle bounds and optimality
- Adaptive risk bounds in univariate total variation denoising and trend filtering
- Local Rademacher complexities and oracle inequalities in risk minimization. (2004 IMS Medallion Lecture). (With discussions and rejoinder)
- Adaptive piecewise polynomial estimation via trend filtering
- Total Variation in Imaging
- Geometric properties of solutions to the total variation denoising problem
- An Upwind Finite-Difference Method for Total Variation–Based Image Smoothing
- Square-root lasso: pivotal recovery of sparse signals via conic programming
- Discrete Total Variation: New Definition and Minimization
- On Sparse Representations in Arbitrary Redundant Bases
- Sparse and Redundant Representations
- On tight bounds for the Lasso
- The DFS Fused Lasso: Linear-Time Denoising over General Graphs
- Sharp Oracle Inequalities for Stationary Points of Nonconvex Penalized M-Estimators
- Sharp Oracle Inequalities for Square Root Regularization
- Sparsity and Smoothness Via the Fused Lasso
- Oracle Inequalities and Minimax Rates for Nonlocal Means and Related Adaptive Kernel-Based Methods
- Analysis versus synthesis in signal priors
- Total Variation Projection With First Order Schemes
- Towards a Mathematical Theory of Super‐resolution
- Metric entropy of high dimensional distributions
- Convex Analysis
