Until somewhat recently, there has been very little investigation into the impact that data volume and source/target domain similarity have played in transfer learning performance; however, it's a topic important to the usability of transfer learning and a topic I've written about. In the paper Investigating the Impact of Data Volume and Domain Similarity on Transfer Learning Applications, (https://arxiv.org/pdf/1712.04008.pdf), written by my colleagues, Yuntao Li, Dingchao Zhang, and myself, we did some experimentation on these topics. Here's what we found.
The impact of source/target volume and similarity
More data is always beneficial
In several experiments conducted by Google researchers in the paper Revisiting...
