Active, Semi-Supervised Learning for Textual Information Access
author:
Anastasia Krithara,
XEROX Research Centre Europe, Xerox
Categories
Top: Computer Science: Information RetrievalTop: Computer Science: Text Mining
Top: Computer Science: Machine Learning: Active Learning
Top: Computer Science: Machine Learning: Semi-supervised Learning
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| Slides | |
| 0:00 | Active, Semi-Supervised Learning for Textual Information Access |
| 0:15 | Introduction pt 1 |
| 1:06 | Introduction pt 2 |
| 1:21 | Outline |
| 1:43 | Semi-Supervised Learning (SSL) |
| 2:12 | Active Learning |
| 3:21 | Combination of SSL and Active Learning |
| 4:25 | Active, Semi-Supervised PLSA pt 1 |
| 4:50 | Active, Semi-Supervised PLSA pt 2 |
| 5:27 | Active, Semi-Supervised PLSA pt 3 |
| 6:18 | Active, Semi-Supervised PLSA pt 4 |
| 8:10 | Active, Semi-Supervised PLSA pt 5 |
| 8:50 | Active, Semi-Supervised PLSA pt 6 |
| 9:15 | Active, Semi-Supervised PLSA pt 7 |
| 9:58 | Experimental Setting pt 1 |
| 10:53 | Experimental Setting pt 2 |
| 11:31 | Experimental Results pt 1 |
| 12:00 | Experimental Results pt 2 |
| 12:13 | Experimental Results pt 3 |
| 12:31 | Conclusions |
| 12:53 | Future Work |
| 13:56 | Thank you |
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great performance, though you seemed very stressed...Obviously you know your subject and you deserve to succeed in you phd!
Kind regards, an old internship friend with a red car... ;-)
a red car with lots of beers (not bear) inside
Good work. SSL + Active Learning makes a lot of sense to combine.
Looks from the preliminary results that SSL is doing most of the heavy lifting. AL helps a little.
I wonder about the more common case where the class of interest is in the minority.