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English(EN) Distinguishability and Recovery for a Doubly Sparse Spiked Wigner Model

新的维格纳模型分析噪声数据中的稀疏信号恢复

一篇新的研究论文介绍了一种双稀疏尖峰维格纳模型,用于分析噪声数据中稀疏信号的可区分性和恢复性。该研究详细介绍了各种算法和参数范围,包括用于在亚高斯噪声下识别信号支持的广义二次阈值程序。研究结果还扩展到具有连续噪声的Rademacher尖峰,提供了在不要求噪声分布矩假设的情况下精确恢复的条件。 AI

排序理由 该集群包含一篇在arXiv上发表的研究论文,详细介绍了一种新的统计模型和算法。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新的维格纳模型分析噪声数据中的稀疏信号恢复

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该集群包含一篇在arXiv上发表的研究论文,详细介绍了一种新的统计模型和算法。[lever_c_demoted from research: ic=1 ai=0.7]
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报道来源 [1]

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

    双稀疏尖峰维格纳模型的可区分性和恢复性

    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…