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Learning from Interpretations: A Rooted Kernel for Ordered Hypergraphs
Published on Jun 23, 20074633 Views
The paper presents a kernel for learning from ordered hypergraphs, a formalization that captures relational data as used in Inductive Logic Programming (ILP). The kernel generalizes previous approache
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Chapter list
Learning from interpretations: A rooted kernel for ordered hypergraphs00:00
Motivation00:40
Agenda01:17
Kernel definition-0101:50
Kernel definition-0202:41
Previous work03:12
Walk types04:17
Graph kernel and variants06:51
Edge kernel-0108:38
Edge kernel-0210:14
Example10:57
A hypergraph kernel-0111:22
A hypergraph kernel-0212:02
Experiments12:47
Edge encoding (Gärtner05)14:12
Edge encoding-0114:56
Edge encoding-0215:05
Edge encoding-0315:17
Edge encoding-0415:29
Edge encoding-0515:33
Edge encoding-0715:37
Edge encoding-0815:40
Experimental setup15:45
Results on NCTRER-0116:15
Results on NCTRER-0216:28
Results-0117:02
Results-0218:01
Results-0318:26
Results-0418:29
Results-0519:38
Results-0619:42
Results-0720:18
Summary20:29
Thank you22:34