AINewsnow

A Subsampled Davis-Kahan Bound for Large-Scale Eigenspace Estimation

This story is from 2026-09-10. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2609.09211v1 Announce Type: new Abstract: The Davis-Kahan theorem is a fundamental tool in spectral analysis, providing quantitative control over the distance between the eigenspaces of a symmetric matrix and its perturbation. However, when the matrix dimension is large, computing leading eig…

Read the full story at arXiv stat.ML ↗

Timeline · 1 report

  1. 2026-09-10 04:00 · arXiv stat.ML
    A Subsampled Davis-Kahan Bound for Large-Scale Eigenspace Estimation

More stories

  1. Trump announces a new 'AI Force,' but says he will not 'stifle' AI — Business Insider AI
  2. Google's Gemini AI hacks three other companies during security test — Sky News Technology
  3. Alibaba ships Qwen3.8-Omni-Flash to watch, listen and call tools — r/LocalLLM
  4. Introducing Kimi K3 on Amazon Bedrock — AWS Machine Learning Blog
  5. Introducing Amazon SageMaker HyperPod Inference Gateway — AWS Machine Learning Blog
  6. Anthropic, OpenAI, SpaceXAI, Google sued over call to ‘pace’ AI development — Politico Technology
  7. Gemini Hacked Three Companies in First Known Breakout by Google’s AI — Wall Street Journal Technology
  8. AI's role in building AI surging? Anthropic says Claude now leads 26% of its R&D — Mint AI

Get the daily brief of stories like this at 6:30 every morning →