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- Title
New ways of solving large Markov chains.
- Authors
Litvak, Nelly
- Abstract
Then, the error term of OPIC is as in (1), but HT <math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>C</mi><mi>t</mi></msub></math> ht will not reduce to zero, and thus the convergence occurs only due to the total transferred cash going to infinity. The algorithm returns the estimation HT <math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mover accent="true"><mi> </mi><mo stretchy="false">^</mo></mover><mrow><mi>t</mi><mo>,</mo><mi>i</mi></mrow></msub></math> ht of HT <math xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi> </mi><mi>i</mi><mo>*</mo></msubsup></math> ht , that is the cash transferred by I i i , divided by the total cash transferred by all states before time I t i . Why does the RLGL algorithm converge to the correct HT <math xmlns="http://www.w3.org/1998/Math/MathML"><msup><mi> </mi><mo>*</mo></msup></math> ht ?.
- Subjects
MARKOV processes; QUEUING theory; WORLD Wide Web; WEB search engines; BRANCHING processes; RANDOM walks; HYPERLINKS
- Publication
Queueing Systems, 2022, Vol 100, Issue 3/4, p217
- ISSN
0257-0130
- Publication type
Article
- DOI
10.1007/s11134-022-09821-3