Profile Entropy: A Fundamental Measure for the Learnability and Compressibility of Distributions
–Neural Information Processing Systems
The profile of a sample is the multiset of its symbol frequencies. We show that for samples of discrete distributions, profile entropy is a fundamental measure unifying the concepts of estimation, inference, and compression.
Neural Information Processing Systems
Oct-2-2025, 21:23:50 GMT
- Country:
- Asia > Afghanistan
- Parwan Province > Charikar (0.04)
- Europe > United Kingdom
- England > Cambridgeshire > Cambridge (0.04)
- North America
- Canada (0.14)
- United States > California
- San Diego County > San Diego (0.04)
- Asia > Afghanistan
- Genre:
- Research Report (0.46)
- Technology:
- Information Technology
- Artificial Intelligence
- Machine Learning (1.00)
- Natural Language (1.00)
- Representation & Reasoning > Uncertainty (0.93)
- Data Science (0.67)
- Information Management (0.68)
- Artificial Intelligence
- Information Technology