Sampling partitions, with applications to redistricting

Date: 

Friday, October 21, 2022, 1:00pm to 2:30pm

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.