pyEasyTL

Introduction

This project is the implementation of EasyTL in Python. The EasyTL paper on the website show this domain adaptation method is intuitive and parametric-free. The MATLAB source code is on this Repo.

• scipy.optimize.linprog is slower than PuLP
• M^(-1/2) = (M^(-1))^(1/2) = scipy.linalg.sqrtm(np.linalg.inv(np.array(cov_src)))
• scipy.linalg.sqrtm will introduce complex number #3549 and cause our Dct parameter to be a complex array.

To Do

• PCA_map in intra_alignment.py
• GFK_map in intra_alignment.py

Dev Log

• 2020/02/25 PuLP type conversion problems (can't convert complex to float) is fixed
• 2020/02/24 write label_prop_v2.py using PuLP
• 2020/02/05 implement get_ma_dist and get_cosine_dist in EasyTL.py (fixed)
• 2020/02/03 more distance measurement in get_class_center
• 2020/01/31 CORAL_map still has some issue. (fixed)
• 2020/01/31 The primitive results of Amazon dataset show that we'v successfully implemented the EasyTL(c).

Reference:

1. Easy Transfer Learning By Exploiting Intra-domain Structures
2. Geodesic Flow Kernel for Unsupervised Domain Adaptation