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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

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