[Adapt] Seminar topic: Introduction & basic application for probabilistic graphical model

[Liu Yi]

Hi, Adapters:

Today, I will give a brief talk about probabilistic graphical model.  Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more.


They are the basis for the state-of-the-art methods in a wide variety of applications, such as medical diagnosis, image understanding, speech recognition, natural language processing, and many, many more. They are also a foundational tool in formulating many machine learning problems.


In this seminar, i will pick some basic knowledge to make you understanding this framework better.


Thanks,

Yi Liu (Áõµt)

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Department of Computer Science and Engineering
Shanghai Jiao Tong University
800 Dongchuan Road, Shanghai, China
Email: liuyi61ly at hotmail.com
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