Volume Ratio, Sparsity, and Minimaxity Under Unitarily Invariant Norms

DOI10.1109/TIT.2015.2487541zbMath1359.94135arXiv1306.3609MaRDI QIDQ2977197

Zongming Ma, Yihong Wu

Publication date: 28 April 2017

Published in: IEEE Transactions on Information Theory (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1306.3609

Mathematics Subject Classification ID

Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

Related Items (8)

Geometric inference for general high-dimensional linear inverse problems ⋮ Estimation of low rank density matrices: bounds in Schatten norms and other distances ⋮ Unnamed Item ⋮ Minimax estimation in sparse canonical correlation analysis ⋮ Statistical and computational limits for sparse matrix detection ⋮ Optimal estimation and computational limit of low-rank Gaussian mixtures ⋮ A general framework for Bayes structured linear models ⋮ Minimax rates in network analysis: graphon estimation, community detection and hypothesis testing

This page was built for publication: Volume Ratio, Sparsity, and Minimaxity Under Unitarily Invariant Norms