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## Distributed randomized PageRank algorithms over unreliable channels

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The PageRank algorithm, employed at Google assigns a measure of importance to each web page for ranking purposes. Recently, we have proposed a distributed randomized approach for this algorithm, where web pages compute their own PageRank by communicating over selected links. Here, the focus is on the effects of unreliability in communication, where random data losses are modeled as an outcome of Markov chains. We provide a generalization of the distributed scheme along with analysis on its convergence.

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