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Multilayer Neural Networks
Published on Sep 13, 201510724 Views
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Chapter list
Stochastic gradient descent14:31
Optimization vs. learning16:26
Offline vs. online20:19
Stochastic Gradient Descent - 120:24
Stochastic Gradient Descent - 220:24
Practical illustration30:17
Subtleties31:46
Improved algorithms33:19
Overview33:23
Second order tricks36:34
Momentum and acceleration37:29
Mini-batches40:33
Modern hardware43:24
Successive LBFGS48:41
Martens HF training49:56
Parallel training of neural nets53:20
Deep networks for complex tasks54:32
How to design computers?59:48
Remember “Perceptrons”01:00:39
Bayesian inference01:03:18
Structured problems01:04:26
Engineering learning systems - 101:04:29
Engineering learning systems - 201:05:15
Interactions01:05:50
Training strategies01:06:28
Graph transformer networks01:08:00
A word reader01:08:41
Normalization and discrimination01:10:10
Probabilistic models01:11:28
Denormalized models - 101:13:40
GTN and CRF01:17:45
Check reader - 101:17:59
Denormalized models - 201:18:58
Check reader - 201:20:15
Graph transduction brick01:20:32
Auxiliary tasks - 101:20:33
Auxiliary tasks - 201:21:03
Example: face recognition01:21:58
Example: NLP tagging - 101:23:32
Example: NLP tagging - 201:23:35
Example: NLP tagging - 301:23:37
Example: NLP tagging - 401:23:38
Example: NLP tagging - 501:23:39
Example: object recognition - 101:23:40
Example: object recognition - 201:24:16
Example: object recognition - 301:24:40
Unsupervised auxiliary tasks01:25:32
Unsupervised learning? - 101:25:43
Unsupervised learning? - 201:27:33
Unsupervised learning? - 301:28:26
Transfer Learning and Reasoning01:28:49
Exploitation01:28:53
Exploration01:29:13
Exploration (my two cents)01:30:03