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How to Teach Support Vector Machine to Learn Vector Outputs
Published on Feb 25, 20076516 Views
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Chapter list
How to teach Support Vector Machine00:02
The “Classical” Support Vector Machine(SVM)01:04
Reinterpretation of the normal vector w01:08
Affine transformation = Linear transformation01:59
Primal problem02:02
Dual problem04:14
Primal problem05:27
Solution06:19
Prediction07:16
Prediction when the labels are implicit07:28
Representation of multiclass output08:03
Vertices of hyper-tetrahedron08:15
Embedding Hierarchy08:56
Methods09:45
WIPO-alpha dataset10:22
Computational times11:05
Multiview learning12:20
Multiview learning13:22
Primal problem14:22
One-class SVM interpretation15:09
Primal problem15:33
Spherical embedding16:07
Embedding Hierarchy18:52
Similarities in a hierarchy19:23
Embedding Hierarchy19:32
WIPO-alpha dataset20:37
Primal problem21:42
To get rid of occurrences of explicit labels ...23:57
Prediction when the labels are implicit24:12