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Discriminative Experimental Design
Published on 2011-11-292670 Views
Since labeling data is often both laborious and costly, the labeled data available in many applications is rather limited. Active learning is a learning approach which actively selects unlabeled data
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Presentation
Discriminative Experimental Design00:00
Outline - 100:10
Active Learning00:20
Our Contribution01:23
Outline - 202:22
Notations02:23
Outline - 302:53
Least-Square SVM Revisited02:54
The Objective Function03:51
The Relationship between DED and TED04:55
Reformulation of DED06:11
The Projection Method07:42
Subproblem 108:45
Subproblem 210:16
Properties of Our Optimization Method10:57
Outline - 411:21
Experimental Setup11:24
Results on Newsgroups Data12:28
Results on Reuters Data13:14
Comparison on Two Optimization Techniques13:29
Outline - 513:58
Conclusion14:00
Thank you14:27