arXiv Artificial Intelligence

Probably Approximately Correct Maximum A Posteriori Inference

1 hour ago 13.08.2026 07:00 👁 1 views
Probably Approximately Correct Maximum A Posteriori Inference

Quick summary

arXiv:2601.16083v2 Announce Type: replace-cross Abstract: Computing the conditional mode of a distribution, better known as the maximum a posteriori (MAP) assignment, is a fundamental task in probabilistic inference. However, MAP is generally intractable, and remains hard even under many common structural constraints and approximation schemes. We take a novel approach inspired by multi-armed bandits, recasting MAP as a best arm identification task. We introduce probably approximately correct (PAC) algorithms for MAP that provide provably optimal solutions in both the fixed-confidence and fixed

Key takeaways

  • arXiv:2601.16083v2 Announce Type: replace-cross Abstract: Computing the conditional mode of a distribution, better known as the maximum a posteriori (MAP) assignment, is a fundamental task in probabilistic inference.
  • However, MAP is generally intractable, and remains hard even under many common structural constraints and approximation schemes.
  • We take a novel approach inspired by multi-armed bandits, recasting MAP as a best arm identification task.

Why it matters

The importance of “Probably Approximately Correct Maximum A Posteriori Inference” will be measured by what changes in practice. User behavior, access conditions, verifiable performance and responsible-use outcomes are the signals worth following.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗