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Incremental and Decremental Training for Linear Classification
Published on Oct 07, 20141792 Views
In classification, if a small number of instances is added or removed, incremental and decremental techniques can be applied to quickly update the model. However, the design of incremental and decreme
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Chapter list
Incremental and Decremental Training for Linear Classication00:00
Outline - 100:10
Outline - 200:15
Incremental and Decremental Training00:16
Why Linear Classication for Incremental and Decremental learning?00:58
Linear Classication01:46
Dual Problems02:26
Incremental and Decremental Learning with Warm Start (1/2)02:39
Incremental and Decremental Learning with Warm Start (2/2)03:09
Outline - 304:17
Analysis on Our Setting04:24
Outline - 404:41
Primal or Dual Problem: Which is Better? 04:43
Primal Initial Objective Value for Incremental Learning - 105:11
Primal Initial Objective Value for Incremental Learning - 205:19
Primal Initial Objective Value for Incremental Learning - 305:23
Dual Initial Objective Value for Incremental Learning - 105:31
Dual Initial Objective Value for Incremental Learning - 205:47
Comparison of Primal and Dual Initial Objective Values (1/2)06:03
Comparison of Primal and Dual Initial Objective Values (2/2)07:03
Decremental Learning Initial Objective Values07:21
Outline - 507:55
Optimization Methods with Warm Start07:58
Optimization Methods in Experiments09:01
Outline - 609:44
Additional Information Requirement09:47
Outline - 710:42
Experiment Setting10:43
Data Sets11:17
Relative Dierence to Optimal Objective Value for Incremental Learning11:36
Incremental Learning12:25
Decremental Learning13:23
Outline - 813:28
Conclusions13:31