Pages that link to "Item:Q4974108"

The following pages link to Information-Theoretic Limits on Sparsity Recovery in the High-Dimensional and Noisy Setting (Q4974108):

Displaying 50 items.

• Sparse microwave imaging: principles and applications (Q362310) (← links)
• Sharp recovery bounds for convex demixing, with applications (Q404302) (← links)
• Sharp support recovery from noisy random measurements by \(\ell_1\)-minimization (Q427066) (← links)
• Sparse regression and support recovery with \(\mathbb{L}_2\)-boosting algorithms (Q466526) (← links)
• Structured, sparse regression with application to HIV drug resistance (Q641120) (← links)
• Tight conditions for consistency of variable selection in the context of high dimensionality (Q741803) (← links)
• High-dimensional model recovery from random sketched data by exploring intrinsic sparsity (Q782446) (← links)
• High-dimensional Gaussian model selection on a Gaussian design (Q985331) (← links)
• On stepwise pattern recovery of the fused Lasso (Q1660156) (← links)
• Sparsity enabled cluster reduced-order models for control (Q1683852) (← links)
• Inferring large graphs using \(\ell_1\)-penalized likelihood (Q1704026) (← links)
• Sobolev duals for random frames and \(\varSigma \varDelta \) quantization of compressed sensing measurements (Q1946588) (← links)
• Minimax risks for sparse regressions: ultra-high dimensional phenomenons (Q1950804) (← links)
• On the asymptotic properties of the group lasso estimator for linear models (Q1951765) (← links)
• Honest variable selection in linear and logistic regression models via \(\ell _{1}\) and \(\ell _{1}+\ell _{2}\) penalization (Q1951794) (← links)
• Detection boundary in sparse regression (Q1952112) (← links)
• The adaptive and the thresholded Lasso for potentially misspecified models (and a lower bound for the Lasso) (Q1952206) (← links)
• Greedy variance estimation for the LASSO (Q2019914) (← links)
• Variable selection consistency of Gaussian process regression (Q2054515) (← links)
• Sparse classification: a scalable discrete optimization perspective (Q2071494) (← links)
• The all-or-nothing phenomenon in sparse linear regression (Q2078961) (← links)
• Sparse regression at scale: branch-and-bound rooted in first-order optimization (Q2097642) (← links)
• Fundamental barriers to high-dimensional regression with convex penalties (Q2119224) (← links)
• Sparse high-dimensional linear regression. Estimating squared error and a phase transition (Q2131259) (← links)
• Iterative algorithm for discrete structure recovery (Q2131266) (← links)
• Fundamental limits of exact support recovery in high dimensions (Q2203616) (← links)
• Which bridge estimator is the best for variable selection? (Q2215760) (← links)
• Sparse regression: scalable algorithms and empirical performance (Q2225311) (← links)
• A discussion on practical considerations with sparse regression methodologies (Q2225315) (← links)
• A numerical exploration of compressed sampling recovery (Q2267399) (← links)
• Minimax posterior convergence rates and model selection consistency in high-dimensional DAG models based on sparse Cholesky factors (Q2284379) (← links)
• Approximation of generalized ridge functions in high dimensions (Q2315030) (← links)
• Preconditioning for orthogonal matching pursuit with noisy and random measurements: the Gaussian case (Q2338338) (← links)
• Minimax-optimal nonparametric regression in high dimensions (Q2343958) (← links)
• Sparse learning via Boolean relaxations (Q2349117) (← links)
• Goodness-of-fit tests for high-dimensional Gaussian linear models (Q2380086) (← links)
• Capturing ridge functions in high dimensions from point queries (Q2428577) (← links)
• Support union recovery in high-dimensional multivariate regression (Q2429923) (← links)
• Penalised robust estimators for sparse and high-dimensional linear models (Q2664993) (← links)
• Recovery of partly sparse and dense signals (Q2692936) (← links)
• Compressive Classification: Where Wireless Communications Meets Machine Learning (Q3460843) (← links)
• (Q4969222) (← links)
• Variable Selection With Second-Generation <i>P</i>-Values (Q5050808) (← links)
• Nonlinear Variable Selection via Deep Neural Networks (Q5066407) (← links)
• Fast Best Subset Selection: Coordinate Descent and Local Combinatorial Optimization Algorithms (Q5144778) (← links)
• Information-Theoretic Limits on Sparse Signal Recovery: Dense versus Sparse Measurement Matrices (Q5281472) (← links)
• On the Fundamental Limits of Recovering Tree Sparse Vectors From Noisy Linear Measurements (Q5346147) (← links)
• Influences of preconditioning on the mutual coherence and the restricted isometry property of Gaussian/Bernoulli measurement matrices (Q5741242) (← links)
• Confidence Intervals for Low Dimensional Parameters in High Dimensional Linear Models (Q5743269) (← links)
• High-dimensional regression with unknown variance (Q5965306) (← links)