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teaching:ss2016:lecture_graphical_models [2016/06/22 10:04] domokos |
teaching:ss2016:lecture_graphical_models [2016/07/18 11:03] (current) domokos |
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Directed and undirected graphical models | Directed and undirected graphical models | ||
- | * Bayesian | + | * Bayesian |
- | * Markov | + | * Markov |
- | * Conditional | + | * Conditional |
Parameter learning for MRF and CRF models | Parameter learning for MRF and CRF models | ||
* Gradient based optimization | * Gradient based optimization | ||
* Stochastic gradient descent | * Stochastic gradient descent | ||
- | * Structured | + | * Structured |
Exact MAP inference methods for MRFs | Exact MAP inference methods for MRFs | ||
- | * Belief propagation on trees: | + | * Belief propagation on trees: |
* Binary graph cuts | * Binary graph cuts | ||
* Branch-and-mincut | * Branch-and-mincut | ||
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** Location:** Room 02.09.023\\ | ** Location:** Room 02.09.023\\ | ||
- | ** 1st Date: | + | ** 1st Date: |
- | ** 2nd Date: | + | ** 2nd Date: |
Please contact us per email if you want to reserve a specific time slot. | Please contact us per email if you want to reserve a specific time slot. |