wjj5881005 / domain_adaptation-1

traditional domain adaptation methods (e.g., GFK, TCA, SA)

This repository contains the source code of the following traditional domain adaptation methods: DASVM, DIP, GFK, KMM, SA, SGF, STM, TCA, and RDALR. Their corresponding paper titles are as follows,

1. DASVM: Domain adaptation problems: A DASVM classification technique and a circular validation strategy

2. DIP: Unsupervised domain adaptation by domain invariant projection

3. GFK: Geodesic flow kernel for unsupervised domain adaptation

4. KMM: Correcting sample selection bias by unlabeled data

5. SA: Unsupervised visual domain adaptation using subspace alignment

6. SGF: Domain adaptation for object recognition: An unsupervised approach

7. STM: Selective transfer machine for personalized facial action unit detection

8. TCA: Domain adaptation via transfer component analysis

9. RDALR: Robust visual domain adaptation with low-rank reconstruction