On signal detection and confidence sets for low rank inference problems
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Publication:902209
DOI10.1214/15-EJS1087zbMath1329.62216arXiv1507.03829MaRDI QIDQ902209
Richard Nickl, Alexandra Carpentier
Publication date: 7 January 2016
Published in: Electronic Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1507.03829
Related Items (3)
Adaptive confidence sets for matrix completion ⋮ Asymptotic frequentist coverage properties of Bayesian credible sets for sieve priors ⋮ Two-sample Hypothesis Testing for Inhomogeneous Random Graphs
Cites Work
- Adaptive confidence sets in \(L^2\)
- Von Neumann entropy penalization and low-rank matrix estimation
- Estimation of (near) low-rank matrices with noise and high-dimensional scaling
- Nuclear-norm penalization and optimal rates for noisy low-rank matrix completion
- On adaptive inference and confidence bands
- Global testing under sparse alternatives: ANOVA, multiple comparisons and the higher criticism
- Nonparametric goodness-of-fit testing under Gaussian models
- Detection boundary in sparse regression
- ROP: matrix recovery via rank-one projections
- Confidence sets in sparse regression
- Mathematical Foundations of Infinite-Dimensional Statistical Models
- Tight Oracle Inequalities for Low-Rank Matrix Recovery From a Minimal Number of Noisy Random Measurements
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