Pages that link to "Item:Q1928276"

The following pages link to The convex geometry of linear inverse problems (Q1928276):

Displaying 29 items.

• The Geometry of Rank-One Tensor Completion (Q5347300) (← links)
• Symmetric Tensor Nuclear Norms (Q5369251) (← links)
• The Alternating Descent Conditional Gradient Method for Sparse Inverse Problems (Q5737722) (← links)
• Low-Rank Tensor Recovery using Sequentially Optimal Modal Projections in Iterative Hard Thresholding (SeMPIHT) (Q5738180) (← links)
• On the Convergence Rate of Projected Gradient Descent for a Back-Projection Based Objective (Q5860373) (← links)
• Signal Decomposition Using Masked Proximal Operators (Q5870789) (← links)
• The basins of attraction of the global minimizers of non-convex inverse problems with low-dimensional models in infinite dimension (Q5878252) (← links)
• Randomized numerical linear algebra: Foundations and algorithms (Q5887823) (← links)
• Greedy Algorithm Almost Dominates in Smoothed Contextual Bandits (Q5890034) (← links)
• Bayesian computation: a summary of the current state, and samples backwards and forwards (Q5963784) (← links)
• Sharp global convergence guarantees for iterative nonconvex optimization with random data (Q6046308) (← links)
• Robust Recovery of Low-Rank Matrices and Low-Tubal-Rank Tensors from Noisy Sketches (Q6066095) (← links)
• A unified approach to uniform signal recovery from nonlinear observations (Q6101267) (← links)
• Asymptotic linear convergence of fully-corrective generalized conditional gradient methods (Q6126647) (← links)
• Sampling rates for \(\ell^1\)-synthesis (Q6142336) (← links)
• Noisy linear inverse problems under convex constraints: exact risk asymptotics in high dimensions (Q6183752) (← links)
• The Lasso with general Gaussian designs with applications to hypothesis testing (Q6183778) (← links)
• Separation-free spectral super-resolution via convex optimization (Q6499003) (← links)
• Reweighted covariance fitting based on nonconvex Schatten-\(p\) minimization for gridless direction of arrival estimation (Q6534404) (← links)
• Effectiveness of the tail-atomic norm in gridless spectrum estimation (Q6567394) (← links)
• Cardinality-constrained structured data-fitting problems (Q6584338) (← links)
• Cardinality minimization, constraints, and regularization: a survey (Q6585278) (← links)
• The stochastic multi-gradient algorithm for multi-objective optimization and its application to supervised machine learning (Q6601525) (← links)
• New low-rank optimization model and algorithms for spectral compressed sensing (Q6616476) (← links)
• Multichannel frequency estimation with constant amplitude via convex structured low-rank approximation (Q6623660) (← links)
• Complementary composite minimization, small gradients in general norms, and applications (Q6634528) (← links)
• Frank-Wolfe-type methods for a class of nonconvex inequality-constrained problems (Q6634538) (← links)
• Deep networks for system identification: a survey (Q6659190) (← links)
• A theory of optimal convex regularization for low-dimensional recovery (Q6663356) (← links)