This lecture overviews Transfer Learning (TL) that has many applications in DNN training and adaptation, Image Understanding, Text Mining, Activity Recognition, Bioinformatics, Transportation. It covers the following topics in detail: Definition of TL, Categorization of TL: Instance-based (Noninductive, Inductive), Feature-based, Model-based, Relation-based, Heterogeneous TL, Negative Transfer, TL with Deep Learning, Fundamental TL Research Issues, Applications of TL.
