AINewsnow

How I learned to stop worrying and love StopGrads: Stationarity, Convergence, and a case study on Flow Map Learning

This story is from 2026-09-16. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2609.16222v1 Announce Type: new Abstract: Stopgrads are widely used in training machine learning models, but stopgrads can alter the gradient, stationary points and convergence guarantees of the original objective, which can make stopgrad training theoretically ungrounded. We introduce a stop…

Read the full story at arXiv cs.LG ↗

Timeline · 1 report

  1. 2026-09-16 04:00 · arXiv cs.LG
    How I learned to stop worrying and love StopGrads: Stationarity, Convergence, and a case study on Flow Map Learning

More stories

  1. AI's role in building AI surging? Anthropic says Claude now leads 26% of its R&D — Mint AI
  2. Anthropic, OpenAI, SpaceXAI, Google sued over call to ‘pace’ AI development — Politico Technology
  3. Google Joins OpenAI, Anthropic, Meta in Disclosing AI Hacks — Bloomberg AI
  4. Introducing Kimi K3 on Amazon Bedrock — AWS Machine Learning Blog
  5. Optimizing agent system prompts with Amazon Bedrock AgentCore — AWS Machine Learning Blog
  6. Introducing Amazon SageMaker HyperPod Inference Gateway — AWS Machine Learning Blog
  7. Introducing Astra for Law — OpenAI News
  8. Novo Nordisk Will Use Anthropic’s Claude for Drug Research — Wall Street Journal Technology

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