New Study Proposes High-Probability Risk Control for Online Policy Learning

A new arXiv paper studies risk control for online policy learning, where an agent adaptively collects data and learns a policy whose risk stays below a tolerable threshold with high probability.

Read the full story at arXiv cs.LG ↗

Timeline · 1 report

2026-11-11 05:00 · arXiv cs.LG
High Probability Risk Control for Online Policy Learning

More stories

Nvidia CEO Jensen Huang faces spy scandal over alleged relationship with Chinese asset Alice Huang — New York Times AI
Anthropic targets $1.4 trillion valuation in IPO, trading expected to begin Nov. 19 — CNBC Technology
Google launches Gemini 4 Carbon across Copilot, API, and Ultra tiers — Google DeepMind Blog
Cognizant Launches Claude Managed Services With 25,000-Strong Frontier Capability Group — Economic Times Tech
OpenAI launches Businesses in ChatGPT in beta with claimable profiles and agents — OpenAI News
TSMC to invest up to $1 billion in Anthropic and OpenAI — Economic Times Tech
STATERA Library Adds Chapters 11-18 on Omni and Steer Drive Robotics — DEV Community — AI
Anthropic expands Claude into a workspace with Sheets, Whiteboards, and Meetings — Anthropic (X)

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