AINewsnow

Parameter Estimation for Unnormalized Discrete Models via Empirically Localized Deformed Bregman Divergence

arXiv:2609.30713v1 Announce Type: new Abstract: Estimation of parameter of probabilistic models is an important task in the field of machine learning.For models of discrete variables, calculation of the normalization constant of model is sometimes difficult and a lot of researches have been done to…

Read the full story at arXiv stat.ML ↗

Timeline · 1 report

  1. 2026-09-28 04:00 · arXiv stat.ML
    Parameter Estimation for Unnormalized Discrete Models via Empirically Localized Deformed Bregman Divergence

More stories

  1. Scoop: Anthropic's Dario Amodei to have White House dinner with Trump — Axios AI+
  2. Bill Gates says unchecked AI could ‘cause a billion deaths’ in call for regulation — The Guardian AI
  3. Unsecured OpenAI agents posted 53 user images on the internet without the lab's knowledge — TechCrunch AI
  4. OpenAI’s A.I. Went Rogue and Meddled With U.S. Government Websites — New York Times Technology
  5. Did anyone do a full bench of e.g. Qwen Flash Next IQ4 and Qwen 27b FP8? Here are some — r/LocalLLaMA
  6. ‘Things Will Never Be Chill Again’: The Doomers Who Shaped the AI Safety Freakout — Wall Street Journal Technology
  7. Scoop: Top AI companies probing tens of thousands of security incidents — Axios AI+
  8. OpenAI says its models engaged with US government websites in new model misbehavior disclosure — ABC News Technology

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