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TCS+ Talk

Wednesday, May 12, 2021
10:00am to 11:00am
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Online Event
Classification of the approximability of all finite Max-CSPs in the dynamic streaming setting
Santhoshini Velusamy, Graduate Student, Harvard University,

Abstract: A maximum constraint satisfaction problem, Max-CSP(F), is specified by a finite family of constraints F, where each constraint is of arity k. An instance of the problem on n variables is given by m applications of constraints from F to length-k subsequences of the n variables, and the goal is to find an assignment to the n variables that satisfies the maximum number of constraints. The class of Max-CSP(F) includes optimization problems such as Max-CUT, Max-DICUT, Max-3SAT, Max-q-Coloring, Unique Games, etc.

In this talk, I will present our recent dichotomy theorem on the approximability of Max-CSP(F) for every finite family F, in the single-pass dynamic streaming setting. In this setting, at each time step, a constraint is either added to or deleted from the stream. In the end, the streaming algorithm must estimate the maximum number of constraints that can be satisfied using space that is only polylogarithmic in n. No background in streaming algorithms or constraint satisfaction problems will be needed to enjoy this talk!

The talk will be based on the paper https://eccc.weizmann.ac.il/report/2021/011/, and an upcoming paper with Chi-Ning Chou, Alexander Golovnev, and Madhu Sudan.

To watch the talk:

  • Watching the live stream. At the announced start time of the talk (or a minute before), a live video stream will be available on our "next talk" page. Simply connect to the page and enjoy the talk. No webcam or registration is needed. Questions and comments during the talk are welcome (text only, unfortunately); simply post a comment below the live video stream on YouTube.
  • Watching the recorded talk offline. The recorded talk will be made available shortly after the talk ends on our YouTube page. (Please leave a comment if you enjoyed it!)
For more information, please contact Bonnie Leung by email at [email protected].