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Algorithms for Lipschitz Learning on Graphs
Published on Aug 20, 20152951 Views
We develop fast algorithms for solving regression problems on graphs where one is given the value of a function at some vertices, and must find its smoothest possible extension to all vertices. The ex
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Chapter list
Algorithms for Lipschitz Learning on Graphs00:00
Learning on Graphs - 100:09
Learning on Graphs - 200:46
The Basics01:14
Preliminaries - 101:18
Preliminaries - 201:26
Preliminaries - 301:32
Preliminaries - 401:33
Preliminaries - 501:58
Two Smooth Extensions - 102:54
Two Smooth Extensions - 203:28
Two Smooth Extensions - 304:00
Two Smooth Extensions - 404:39
Two Smooth Extensions - 504:50
Two Smooth Extensions - 604:54
Other Smooth Extensions05:02
Concern with 2-Minimizer05:43
2-Minimizer vs Lex06:22
Other Smooth Extensions07:09
Algorithms07:35
Some Definitions07:44
Steepest Terminal PAir09:04
Finding a Steepest Pair09:59
Simple Case: Star Graph10:33
Directed Graphs11:26
Stability and Regularization12:18
Noise Stability12:21
l1 Regularization 12:49
l0 Regularization 13:36
Experiments14:24
Fast Implementations14:34
Detecting Spam Webpages - 115:09
Detecting Spam Webpages - 216:30
Comparison16:48
Conclusion17:39