Abstract
An on-line learning algorithm for probability distributions is constructed in a reparameterization invariant form. It enables us to identify the distributions which transform from one to another by reparameterization. This is an essential property not only for pattern recognition problems but also for the property of `information'. We can find the algorithm to be optimal, since conformal gauge reduces the problem to a non-covariant case.
Original language | English |
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Pages | 175-180 |
Number of pages | 6 |
DOIs | |
Publication status | Published - 2000 |
Externally published | Yes |
Event | International Joint Conference on Neural Networks (IJCNN'2000) - Como, Italy Duration: Jul 24 2000 → Jul 27 2000 |
Other
Other | International Joint Conference on Neural Networks (IJCNN'2000) |
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City | Como, Italy |
Period | 7/24/00 → 7/27/00 |
ASJC Scopus subject areas
- Software
- Artificial Intelligence