arXiv (All)
open access
Regret Bounds for Robust Online Decision Making
We propose a framework which generalizes "decision making with structured observations" by allowing robust (i.e. multivalued) models. In this framework, each model associates each decision with a convex set of probability distributions over outcomes. Nature can choose distributions out of this set i
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Fair equality of chances for prediction-based decisions#706235
- Risk-aware Markov decision processes using cumulative prospect theory#1066580
- KTO: Model Alignment as Prospect Theoretic Optimization#984793
- Beyond Answer Confidence: A Controlled Audit of Self-Knowledge in a Black-Box Decision Model#1155941
- A Unified Optimism-Agnostic Framework for Linear Bandits over Spherical Action Sets#1116480
Record · ID 1116093
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive