AINewsnow

Convergence Rates of Gaussian Process Thompson Sampling for Efficient Global Optimization

arXiv:2610.19925v1 Announce Type: new Abstract: Efficient global optimization aims to identify a global optimum of an expensive black-box function within a limited evaluation budget $N$. We investigate the convergence rates of Gaussian process Thompson sampling (GP-TS) under noiseless observations,…

Read the full story at arXiv stat.ML ↗

Timeline · 1 report

  1. 2026-10-15 04:00 · arXiv stat.ML
    Convergence Rates of Gaussian Process Thompson Sampling for Efficient Global Optimization

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 →