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Relations Betweeen Machine Learning Problems
Published on Jan 25, 20128842 Views
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Chapter list
Relations Betweeen Machine Learning Problems00:00
Why this workshop? - 100:05
Why this workshop? - 200:23
Why this workshop? - 300:32
Why this workshop? - 400:43
Analogy - 101:51
Analogy - 202:23
The 20th Century View. . .02:34
(One possible) Goal - 103:11
(One possible) Goal - 203:21
Why “relations” rather than “attributes”? - 103:39
Why “relations” rather than “attributes”? - 204:09
Why “relations” rather than “attributes”? - 304:47
Grothendieck’s Relative Point of View04:57
Why “problems” and not “algorithms”05:49
Problem oriented versus method oriented - 107:32
Problem oriented versus method oriented - 208:13
Problem oriented versus method oriented - 308:23
A flood of problems - 108:36
A flood of problems - 208:56
Studying relations between ML problems is not new. . .09:39
Lots of Existing Relations - 110:14
Lots of Existing Relations - 210:38
Lots of Existing Relations - 311:04
Lots of Existing Relations - 411:26
Lots of Existing Relations - 512:51
Not just “reductions”13:26
Types of Relations14:11
Monocausotaxophilia considered harmful - 114:47
Monocausotaxophilia considered harmful - 214:59
Standards and Modularisation16:48
Not just a theoretical exercise! - 119:32
Not just a theoretical exercise! - 219:41
Not just a theoretical exercise! - 320:05
Not just a theoretical exercise! - 420:09
Not just a theoretical exercise! - 520:17
Not just a theoretical exercise! - 620:30
Desired Outcomes - 120:32
Desired Outcomes - 221:01
Desired Outcomes - 322:04
Desired Outcomes - 422:17
Desired Outcomes - 523:08
Desired Outcomes - 623:10