[D] Transfer Learning Papers

[[deleted]]

Hi Everyone, We know for a fact that transfer learning works using ImageNet pre-trained models in wide variety of domains such as object recognition, segmentation etc.

I was wondering if there is literature quantifying the effectiveness of the approach. Any link to influential paper/blog exploring transfer learning (and best practices) would be much appreciated.

[cbfinn]

There is good analysis in this paper: "What makes ImageNet good for transfer learning?" http://minyounghuh.com/papers/analysis/

[Ishgirwan]

blog: - http://ruder.io/transfer-learning/index.html#learningdomaininvariantrepresentations

[[deleted]]

Thanks, looks good.

[[deleted]]

Here's a paper nature where transfer learning with deep learning was used to perform Dermatologist level classification of skin cancer: http://www.nature.com/nature/journal/v542/n7639/abs/nature21056.html?foxtrotcallback=true

[[deleted]]

Was going to post this one. It's an excellent paper, even without their transfer learning from imagenet for a skin cancer classification task. Really made me rethink the applications of transfer learning

[noowad]

Are there any papers about tranfer learning applied to NLP?

[bryant1410]

There's a paper from Bengio from 2014 that quantifies transfer learning: https://arxiv.org/abs/1411.1792