AINewsnow

On Inherent Privacy of Posterior Sampling: A Unified R\'enyi-Divergence Framework

arXiv:2610.19573v1 Announce Type: new Abstract: Differential Privacy (DP) provides a rigorous framework for quantifying privacy guarantees. While most methods achieve DP by injecting calibrated random noise, the intrinsic randomness of certain procedures such as sampling can yield DP guarantees ``f…

Read the full story at arXiv stat.ML ↗

Timeline · 1 report

  1. 2026-10-15 04:00 · arXiv stat.ML
    On Inherent Privacy of Posterior Sampling: A Unified R\'enyi-Divergence Framework

More stories

  1. OpenAI engineer charged with planting surveillance device in office — Sky News Technology
  2. Anthropic reports $16.8 billion Q3 revenue ahead of planned IPO — Bloomberg AI
  3. Eight US states sue OpenAI over alleged safety risks to children — The Verge AI
  4. MIT Professor Explores AI's Impact on Thinking Skills in New Book — MIT News AI
  5. SK Hynix and Samsung shares plunge amid tech sell-off — CNBC Technology
  6. Figma introduces agent features and open beta for code layers — TechCrunch AI
  7. Meta Study: Most Small Businesses Use AI for Productivity — Meta Newsroom
  8. Google and Meta launch new frontier AI models amid competitive benchmarking — Google Gemini Blog

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