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<p class="MsoNormal"><span style="color:#212121">This is an announcement of<span class="apple-converted-space"> </span><span class="outlook-search-highlight">Erasmo</span><span class="apple-converted-space"> </span><span class="outlook-search-highlight">Tani</span>'s
MS Presentation<br>
===============================================<br>
Candidate:<span class="apple-converted-space"> </span><span class="outlook-search-highlight">Erasmo</span><span class="apple-converted-space"> </span><span class="outlook-search-highlight">Tani</span><br>
<br>
Date: November 20,2023<br>
<br>
Time: 12:00pm<br>
<br>
Remote Location:<span class="apple-converted-space"> </span><a href="https://urldefense.com/v3/__https:/uchicago.zoom.us/j/92432425198?pwd=QjMxZm1jMGZlT2NRaS84SWlwQjJrUT09__;!!BpyFHLRN4TMTrA!-0negPD-Q9O8q7rjtAe1FXIpu3P92TCqfwE14UC4lOAQ20dZjwi_HtrQpzJdBOzufi_7pUr5hiMHOTlCi3RB1Q$" title="https://urldefense.com/v3/__https://uchicago.zoom.us/j/92432425198?pwd=QjMxZm1jMGZlT2NRaS84SWlwQjJrUT09__;!!BpyFHLRN4TMTrA!-0negPD-Q9O8q7rjtAe1FXIpu3P92TCqfwE14UC4lOAQ20dZjwi_HtrQpzJdBOzufi_7pUr5hiMHOTlCi3RB1Q$"><span style="color:#0078D7">https://uchicago.zoom.us/j/92432425198?pwd=QjMxZm1jMGZlT2NRaS84SWlwQjJrUT09</span></a><br>
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Location: JCL 298<br>
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M.S. Paper Title: PageRank: Old and New.<br>
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Abstract: In a seminal paper from 1998, Brin et al. introduced PageRank, an algorithm to conduct link analysis of the web graph, ranking webpages based on a notion of authority. Since its first appearance, PageRank has found numerous applications even outside
the web and has become an essential algorithmic primitive. We will first survey different interpretations of the PageRank vector as well as some of its fundamental computational aspects in the classical setting of undirected graphs. We will then describe a
way to extend PageRank to hypergraphs. In this more general setting, we will discuss connections with the theory of semigroups and how these connections allow for the design of fast algorithms to approximately compute hypergraph personalized PageRank vectors.
The presentation will be largely based on recent work by Ameranis et al..<br>
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Advisors: Lorenzo Orecchia<br>
<br>
Committee Members: Yury Makarychev, Lorenzo Orecchia, Ali Vakilian<o:p></o:p></span></p>
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