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New Wigner Model Analyzes Sparse Signal Recovery in Noisy Data

By PulseAugur Editorial · [1 sources] ·

A new research paper introduces a doubly sparse spiked Wigner model to analyze the distinguishability and recovery of sparse signals within noisy data. The study details various algorithms and parameter regimes, including a generalized quadratic thresholding procedure for identifying signal support under sub-Gaussian noise. The findings also extend to Rademacher spikes with continuous noise, providing conditions for exact recovery without requiring moment assumptions on the noise distribution. AI

RANK_REASON The cluster contains a research paper published on arXiv detailing a new statistical model and algorithms. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New Wigner Model Analyzes Sparse Signal Recovery in Noisy Data

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The cluster contains a research paper published on arXiv detailing a new statistical model and algorithms. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Ioana Dumitriu, JD Flynn, Zhichao Wang ·

    Distinguishability and Recovery for a Doubly Sparse Spiked Wigner Model

    arXiv:2610.23033v1 Announce Type: cross Abstract: We study distinguishability and recovery of a sparse rank-one signal in a spiked Wigner model with independently sparse noise through a variety of algorithms and parameter regimes. The signal and noise have separate sparsity param…

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