scientific article; zbMATH DE number 6860803

zbMath1441.65049arXiv1707.00622MaRDI QIDQ4637013

Vaneet Aggarwal, Morteza Ashraphijuo, Xiaodong Wang

Publication date: 17 April 2018

Full work available at URL: https://arxiv.org/abs/1707.00622

Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.

zbMATH Keywords

tensormanifoldmatrixrank estimationCP ranklow-rank data completionTucker rankmulti-view matrixtensor-train rank

Mathematics Subject Classification ID

Computational aspects of data analysis and big data (68T09) Numerical methods for low-rank matrix approximation; matrix compression (65F55)

Related Items (5)

Unnamed Item ⋮ Stability Approach to Regularization Selection for Reduced-Rank Regression ⋮ Characterization of sampling patterns for low-tt-rank tensor retrieval ⋮ Fundamental conditions on the sampling pattern for union of low-rank subspaces retrieval ⋮ Unnamed Item

Uses Software

• Jellyfish
• PhaseLift

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Multiarray signal processing: tensor decomposition meets compressed sensing
• Parallel stochastic gradient algorithms for large-scale matrix completion
• Exact matrix completion via convex optimization
• A Singular Value Thresholding Algorithm for Matrix Completion
• Tensor completion and low-n-rank tensor recovery via convex optimization
• The Power of Convex Relaxation: Near-Optimal Matrix Completion
• Fundamental Conditions for Low-CP-Rank Tensor Completion
• Low-rank matrix completion using alternating minimization
• Phase Retrieval via Matrix Completion

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