Abstract:Machine learning (ML) is a data intensive process. For training of ML algorithms huge datasets are required.There are times when enough data is not available due to multitude of reasons. This could be due to lack ofavailability of annotated data in a particular domain or paucity of time in data collection process resulting innon-availability of enough data. Many a times data collection is very expensive and in few domains data collectionis very difficult. In such cases, if methods can be designed to reuse the … Show more
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