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  <title><![CDATA[ARC Colloquium: Aaron Sidford (Stanford)]]></title>
  <body><![CDATA[<p align = "center"><strong>Algorithms &amp; Randomness Center (ARC)</strong></p>

<p align = "center"><strong>Aaron Sidford (Stanford)</strong></p>

<p align = "center"><strong>Monday, October 4, 2021</strong></p>

<p align = "center"><strong>Klaus 1116 East - 11:00 am</strong></p>

<p>&nbsp;</p>

<p><strong>Title:&nbsp; </strong>Recent Advances on the Maximum Flow Problem<em> </em></p>

<p><strong>Abstract: </strong>The maximum flow problem is an incredibly well-studied problem in combinatorial optimization. The problem encompasses a range of cut, matching, and scheduling problems and is a key a proving ground for new techniques in continuous optimization and algorithmic graph theory. In this talk I will survey recent, provably faster algorithms for solving this problem. Further, I will highlight how recent advances in solving mixed l2-lp flows can be coupled with interior point methods to obtain improved running times for solving the problem on unit-capacity graphs. The maximum flow problem on unit capacity graphs encompasses fundamental combinatorial optimization problems including bipartite matching and computing disjoint paths and I will discuss how this line of work has led to state-of-the-art, almost m^(4/3) time algorithms for solving these problems on m-edge graphs. This talk focuses on joint work with Yang P. Liu and Tarun Kathuria.</p>

<p>----------------------------------</p>

<p><a href="https://web.stanford.edu/~sidford/">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></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>
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