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On the Usefulness of Similarity based Projection Spaces for Transfer Learning
Published on 2011-10-176415 Views
Similarity functions are widely used in many machine learning or pattern recognition tasks. We consider here a recent framework for binary classifi cation, proposed by Balcan et al., allowing to lea
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Presentation
On the Usefulness of Similarity based Projection Spaces for Transfer Learning00:00
Introduction and Motivation00:00
Outline00:53
Outline: A Transfer Learning Task01:25
Formalisation01:28
Studied case - 102:16
Studied case - 202:54
Studied case - 302:59
S. Ben-David et al. results - 103:14
S. Ben-David et al. results - 203:29
S. Ben-David et al. results - 303:39
S. Ben-David et al. results - 404:08
S. Ben-David et al. results - 504:36
Outline: Learning with Good Similarity Functions (SF)04:53
Good Similarity Functions04:53
Properties05:41
Outline:Modifying the Projection Space for Domain Adaptation06:31
Modifying the Projection Space for Domain Adaptation: An Heuristic Normalization06:31
An Heuristic Normalization of a Similarity Function06:38
Modifying the Projection Space for Domain Adaptation: An Additional Regularization Term07:23
An Additional Regularization Term For Moving Closer the Two Distributions - 107:33
An Additional Regularization Term For Moving Closer the Two Distributions - 207:43
An Additional Regularization Term For Moving Closer the Two Distributions - 308:21
An Additional Regularization Term For Moving Closer the Two Distributions - 409:05
An Additional Regularization Term For Moving Closer the Two Distributions - 509:28
An Additional Regularization Term For Moving Closer the Two Distributions - 609:37
An Additional Regularization Term For Moving Closer the Two Distributions - 709:56
Reverse Classi er hr and Validation - 110:08
Reverse Classi er hr and Validation - 210:26
Reverse Classi er hr and Validation - 310:36
Reverse Classi er hr and Validation - 410:41
Reverse Classi er hr and Validation - 510:45
Reverse Classi er hr and Validation - 610:54
Reverse Classi er hr and Validation - 711:00
Outline: Experimentations11:13
Experimental Setup11:18
Inter-twinning moons: results12:22
Inter-twinning moons: estimation of the similarity function goodness on TS12:56
Images corpus: results14:05
Outline: Extended Work: A Little Bit of Theory14:25
Sparsity Analysis14:37
Generalization Bounds15:29
Outline: Conclusion and Perspectives16:16
Conclusion and Perspectives16:18
Thank you for your attention.17:13