2006/05/03 by Giacomo Aletti, Aletti, Giacomo · 2 citations
Computer Science · Mathematics · #60J22 #90C35 #94C15 #Additive Markov chain #Advanced Database Systems and Queries #Algorithm #Chain (unit) #Computer science #Discrete mathematics #Distributed systems and fault tolerance #Examples of Markov chains #FOS: Mathematics #Machine learning #Markov chain #Markov chain mixing time #Markov kernel #Markov model #Markov process #Markov property #Markov renewal process #Mathematical optimization #Mathematics #Optimization and Search Problems #Physics #Probability (math.PR) #Programming language #Set (abstract data type) #Statistics #Variable-order Markov model #math.PR #msc:60J22 #msc:90C35 #msc:94C15
paper · pdf · doi:10.48550/arxiv.math/0605099
published in arXiv (Cornell University) (Cornell University) · 8 pages, 1 figure
openalex publication_date 2006/05/03 · arxiv created 2006/06/23 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Given a strongly stationary Markov chain and a finite set of stopping rules, we prove the existence of a polynomial algorithm which projects the Markov chain onto a minimal Markov chain without redundant information. Markov complexity is hence defined and tested on some classical problems.