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  <title><![CDATA[ARC Colloquium:  Yang Liu (Stanford)]]></title>
  <body><![CDATA[<p align = "center"><strong>Algorithms &amp; Randomness Center (ARC)</strong></p>

<p align = "center"><strong>Yang Liu&nbsp; (Stanford)</strong></p>

<p align = "center"><strong>Monday, March 14, 2022</strong></p>

<p align = "center"><strong>Klaus 1116 - 11:00 am</strong></p>

<p>&nbsp;</p>

<p><strong>Title:</strong>&nbsp;<strong>&nbsp;</strong>Maximum Flow and Minimum-Cost Flow in Almost-Linear Time</p>

<p><strong>Abstract:</strong> We give an algorithm that computes exact maximum flows and minimum-cost flows on directed graphs with $m$ edges and polynomially bounded integral demands, costs, and capacities in $m^{1+o(1)}$ time. Our algorithm builds the flow through a sequence of $m^{1+o(1)}$ approximate undirected minimum-ratio cycles, each of which is computed and processed in amortized $m^{o(1)}$ time using a dynamic data structure.</p>

<p>Our framework extends to an algorithm running in $m^{1+o(1)}$ time for computing flows that minimize general edge-separable convex functions to high accuracy. This gives an almost-linear time algorithm for several problems including entropy-regularized optimal transport, matrix scaling, $p$-norm flows, and isotonic regression.</p>

<p>Joint work with Li Chen, Rasmus Kyng, Richard Peng, Maximilian Probst Gutenberg, and Sushant Sachdeva.</p>

<p>---------------------------------------------------------------</p>

<p><a href="https://yangpliu.github.io/">Speaker&#39;s Webpage</a></p>

<p><em>Videos of recent talks are available at: </em><a href="https://smartech.gatech.edu/handle/1853/46836"><em>https://smartech.gatech.edu/handle/1853/46836</em></a><em> and <a href="http://arc.gatech.edu/node/121">http://arc.gatech.edu/node/121</a> </em></p>

<p><a href="https://mailman.cc.gatech.edu/mailman/listinfo/arc-colloq"><em>Click here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu</em></a></p>

<p>&nbsp;</p>
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