#   Sampling partitions, with applications to redistricting 

 



####  calendar\_today Date and Time 

 **October 21, 2022** 

 01:00PM - 02:30PM EDT 

####  pin\_drop Location 

 **SEC 1.413, and streamed via Zoom at: https://harvard.zoom.us/j/95184948637?pwd=bXBIc2U5MEZ0QmRUb01WQ0o0SXRCdz09**  



 

 



 

 Speaker: **Moon Duchin** from the MGGG Redistricting Lab at Tufts. She will be speaking **in-person** on:

 *Sampling partitions, with applications to redistricting*

 Abstract: In the world of gerrymandering, there are many reasons to want to take a “representative sample” of the space of balanced graph partitions — that is, a sample pulled from a known distribution which is clearly relevant to the political districting problem. There are numerous Markov chain methods, plus sequential Monte Carlo, plus a direct tree decomposition method, at least. I’ll discuss this modeling problem at a high level, and will also offer some tools and diagnostics for comparisons.



 

 



 

 See also:- [ Fall 2022 Econ CS Seminars ](/taxonomycalendarseminar/fall-2022)
 
 

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