Pages that link to "Item:Q2400255"
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The following pages link to Low rank tensor recovery via iterative hard thresholding (Q2400255):
Displaying 45 items.
- Minimum \( n\)-rank approximation via iterative hard thresholding (Q299732) (← links)
- Low-rank tensor completion by Riemannian optimization (Q398628) (← links)
- Tensor networks and hierarchical tensors for the solution of high-dimensional partial differential equations (Q506609) (← links)
- Dimensionality reduction with subgaussian matrices: a unified theory (Q515989) (← links)
- Randomized interpolative decomposition of separated representations (Q728743) (← links)
- Cross: efficient low-rank tensor completion (Q1731066) (← links)
- On polynomial time methods for exact low-rank tensor completion (Q2007852) (← links)
- Modified iterations for data-sparse solution of linear systems (Q2042261) (← links)
- Tensor theta norms and low rank recovery (Q2048814) (← links)
- An optimal statistical and computational framework for generalized tensor estimation (Q2119217) (← links)
- Inference for low-rank tensors -- no need to debias (Q2131273) (← links)
- Characterization of sampling patterns for low-tt-rank tensor retrieval (Q2202522) (← links)
- Iterative \(p\)-shrinkage thresholding algorithm for low Tucker rank tensor recovery (Q2212078) (← links)
- The convergence guarantee of the iterative hard thresholding algorithm with suboptimal feedbacks for large systems (Q2275173) (← links)
- Variational Monte Carlo -- bridging concepts of machine learning and high-dimensional partial differential equations (Q2305540) (← links)
- RIP-based performance guarantee for low-tubal-rank tensor recovery (Q2306402) (← links)
- Gradient-based optimization for regression in the functional tensor-train format (Q2312177) (← links)
- Non-intrusive tensor reconstruction for high-dimensional random PDEs (Q2324350) (← links)
- An iterative method for tensor inpainting based on higher-order singular value decomposition (Q2338316) (← links)
- Adaptive iterative hard thresholding for low-rank matrix recovery and rank-one measurements (Q2693686) (← links)
- Low-rank approximation and completion of positive tensors (Q2827064) (← links)
- Quantized Compressed Sensing: A Survey (Q3296175) (← links)
- Geometric Methods on Low-Rank Matrix and Tensor Manifolds (Q3300541) (← links)
- Variants of Alternating Least Squares Tensor Completion in the Tensor Train Format (Q3447473) (← links)
- Tensor Completion in Hierarchical Tensor Representations (Q3460842) (← links)
- Polynomial approximation via compressed sensing of high-dimensional functions on lower sets (Q4605704) (← links)
- Sampling-free Bayesian inversion with adaptive hierarchical tensor representations (Q4634763) (← links)
- Convergence bounds for empirical nonlinear least-squares (Q5034774) (← links)
- Tensor Regression Using Low-Rank and Sparse Tucker Decompositions (Q5037550) (← links)
- Nonconvex Low-Rank Tensor Completion from Noisy Data (Q5080674) (← links)
- $N$-Dimensional Tensor Completion for Nuclear Magnetic Resonance Relaxometry (Q5108470) (← links)
- Jointly low-rank and bisparse recovery: Questions and partial answers (Q5220065) (← links)
- Endpoint Results for Fourier Integral Operators on Noncompact Symmetric Spaces (Q5230191) (← links)
- Low-Rank Tensor Recovery using Sequentially Optimal Modal Projections in Iterative Hard Thresholding (SeMPIHT) (Q5738180) (← links)
- Lower Memory Oblivious (Tensor) Subspace Embeddings with Fewer Random Bits: Modewise Methods for Least Squares (Q5857850) (← links)
- New Riemannian Preconditioned Algorithms for Tensor Completion via Polyadic Decomposition (Q5863880) (← links)
- The numerics of phase retrieval (Q5887821) (← links)
- Tensor completion by multi-rank via unitary transformation (Q6042617) (← links)
- Algebraic compressed sensing (Q6042618) (← links)
- Iterative hard thresholding for low CP-rank tensor models (Q6042723) (← links)
- Pricing High-Dimensional Bermudan Options with Hierarchical Tensor Formats (Q6159076) (← links)
- Modewise operators, the tensor restricted isometry property, and low-rank tensor recovery (Q6172173) (← links)
- Iterative singular tube hard thresholding algorithms for tensor recovery (Q6587556) (← links)
- Approximating the stationary Bellman equation by hierarchical tensor products (Q6616995) (← links)
- Sample complexity bounds for the local convergence of least squares approximation (Q6649924) (← links)
