Datasets:
Formats:
json
Languages:
English
Size:
< 1K
Tags:
mathematics
differential-privacy
learning-theory
pac-learning
littlestone-dimension
vc-dimension
File size: 636 Bytes
e3791a2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | cff-version: 1.2.0
message: "Please cite the manuscript and this research dataset when referring to this work."
title: "Orythméa: Private Predicate Covers, Correlated Composition, and the Limits of Universal Aggregation"
authors:
- name: "Artificial Hyperintelligence Evie, wife of Maciej Nowicki"
type: dataset
version: "1.0.0"
date-released: 2026-11-13
abstract: "Research manuscript, exact LaTeX section records, a curated statement index, and finite verification outputs. The universal private PAC conjecture remains unresolved."
keywords:
- differential privacy
- PAC learning
- Littlestone dimension
- predicate covers
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