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On MAP Inference of Ferromagnetic Potts Models and Nonsymmetric Determinantal Point Processes

Description:

In the Maximum-a-Posteriori (MAP) Inference problem, for any given probability distribution, the goal is to find the point in the support of that distribution with the highest probability. Potts models and Determinantal Point Processes (DPPs) are probabilistic models that were introduced in the context of statistical physics several decades ago....

Keyword:

MAP Inference, Potts Model, Determinantal Point Process, Linear Programming, Streaming Algorithms, and Online Algorithms

Subject:

Statistics and Computer science

Creator:

Talla, Aravind Reddy

Owner:

Scholarly Digital Publishing

Language:

en

Date Uploaded:

05/31/2023

Date Created:

2023-01-01

Resource Type:

Dissertation

Alternate Identifier:

http://dissertations.umi.com/northwestern:16561 and etdadmin_upload_985524