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About Probabilistic Graphical Models: David Sontag
The document summarizes David Sontag's lecture on probabilistic graphical models at NYU on January 31, 2013. The lecture introduced probabilistic graphical models as a powerful approach for reasoning under uncertainty and performing inference based on local observations. It discussed key challenges in representing joint distributions over random variables, learning distributions from data, and performing inference to compute conditional distributions. The lecture also provided an overview of the course syllabus which will cover representation, inference, and learning techniques for graphical models with both discrete and continuous variables.
Detailed Information
| Author: | ['Mishal Thuri'] |
|---|---|
| Publication Year: | 2017 |
| Pages: | 44 |
| Language: | English |
| Format: | |
| Price: | FREE |
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