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Undirected Graphical Models
Published on Sep 13, 201511593 Views
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Chapter list
Undirected Graphical Models00:00
(Undirected) Graphical Models00:54
Probabilistic Graphical Models - 101:51
Probabilistic Graphical Models - 202:45
Probability Review: Conditional Independence04:08
Types of Graphical Models - 106:12
Representing Conditional Independence15:33
Why Undirected Graphical Models?15:38
Conditional Independence Properties18:59
Markov Blanket20:29
Relating Directed and undirected Models21:31
Parametrizing directed Graphical Models33:13
Parametrizing Markov Networks: Factors34:06
Parametrizing Markov Networks: Joint Distribution36:07
Cliques and maximal Cliques38:54
Of Graphs and Distributions40:12
Types of Graphical Models - 241:15
Types of Graphical Models - 343:02
Relating Directed and Undirected Models43:10
Energy-Based Models44:46
Log-Linear Model46:58
Maximum Likelihood Learning - 148:31
Maximum Likelihood Learning - 251:17
Maximum Likelihood Learning - 352:50
Maximum Likelihood Learning - 453:39
Restricted Boltzmann Machines55:48
Restricted Boltzmann Machine - 155:56
Markov Network View - 157:08
Markov Network View - 257:34
Restricted Boltzmann Machine - 257:51
Inference - 157:58
Inference - 259:48
Inference - 301:00:24
Free Energy - 101:02:50
Free Energy - 201:02:54
Restricted Boltzmann Machine - 301:03:02
Maximum Likelihood Training01:03:50
Contrastive Divergence (CD) - 101:06:23
Contrastive Divergence (CD) - 201:08:16
Contrastive Divergence (CD) - 301:09:01
Training01:09:15
Derivation of the Learning Rule - 101:11:11
Derivation of the Learning Rule - 201:11:40
Derivation of the Learning Rule - 301:12:23
CD-K: Pseudocode01:13:12
Contrastive Divergence (CD) - 401:13:58
Persistent CD (PCD)01:15:01
Example of Data Set: MNIST01:17:31
Filters - 101:19:02
Restricted Boltzmann Machine - 401:19:14
Gaussian-Bernoulli RBM01:19:16
Filters - 201:20:39
Spike-and-Slab RBM - 101:21:01
Spike-and-Slab RBM - 201:21:27
ssRBM Inference and Learning01:21:53