mlsanityData to 14 Oct 2026

Noisy Low Rank Column-wise Sensing

arXiv 2409.08384 ↗First posted 12 Sep 2024eess.SP cs.LGcited by 2

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Abstract (arXiv)

This letter studies the AltGDmin algorithm for solving the noisy low rank column-wise sensing (LRCS) problem. Our sample complexity guarantee improves upon the best existing one by a factor max(r, log(1/ε))/r where r is the rank of the unknown matrix and ε is the final desired accuracy. A second contribution of this work is a detailed comparison of guarantees from all work that studies the exact same mathematical problem as LRCS, but refers to it by different names.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 1 of its 10 references that are in the map. First posted on arXiv 12 Sep 2024.

Builds on

1 of 10 references.

References · 1

  1. 2021Exploiting Shared Representations for Personalized Federated Learningcited by 541

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 2026RepUCB: Representation Learning-Based UCB for Heterogeneous Multi-Task Linear Banditscited by 0
  2. 2026Multi-Task Representation Learning for Conservative Linear Banditscited by 0