๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Stochastic Analog Networks and Computational Complexity

โœ Scribed by Hava T. Siegelmann


Publisher
Elsevier Science
Year
1999
Tongue
English
Weight
236 KB
Volume
15
Category
Article
ISSN
0885-064X

No coin nor oath required. For personal study only.


๐Ÿ“œ SIMILAR VOLUMES


Networks and complexity
โœ D. R. White ๐Ÿ“‚ Article ๐Ÿ“… 2002 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 37 KB
The computational complexity of probabil
โœ Gregory F. Cooper ๐Ÿ“‚ Article ๐Ÿ“… 1990 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 708 KB

Bayesian belief networks provide a natural, efficient method for representing probabilistic dependencies among a set of variables. For these reasons, numerous researchers are exploring the use of belief networks as a knowledge representation m artificial intelligence. Algorithms have been developed

Abstract computational complexity and cy
โœ Giorgio Ausiello ๐Ÿ“‚ Article ๐Ÿ“… 1971 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 424 KB

A weakening of Blum's Axioms for abstract computational complexity is introduced in order to take into a better account measures that can be finite even when the computations diverge. How the new axioms affect the theory and how they can be used to get an insight in the theory of computations using

Resource bounded randomness and computat
โœ Yongge Wang ๐Ÿ“‚ Article ๐Ÿ“… 2000 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 165 KB

The following is a survey of resource bounded randomness concepts and their relations to each other. Further, we introduce several new resource bounded randomness concepts corresponding to the classical randomness concepts, and show that the notion of polynomial time bounded Ko randomness is indepen