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Discriminative Experimental Design
Published on Nov 29, 20112659 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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Chapter list
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