arXiv (OAI Expanded)
open access
Minimax bounds for watermarked and masked recursive discrete distribution estimation
Watermarking has been proposed as a way to identify synthetic samples in estimation settings where no metadata is available to distinguish them from real samples, but its precise effects remain unexplored. In the absence of a distinguishing mechanism, it has been shown that adding synthetic samples
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
- Minimax bounds for watermarked and masked recursive discrete distribution estimation#819115
- Minimax bounds for watermarked and masked recursive discrete distribution estimation#622511
- Information-Theoretic Foundations of the AaroNet Multi-Scale Detector#237194
- CertMark: Distortion-Free Multi-Bit Watermarking with Certified Decoding#1118044
- Tight Sample Bounds for Renyi and Min-Entropy Estimation#625535
Record · ID 809123
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