# A Mathematical Framework for Quantifying Transferability in Multi-source Transfer Learning

This repository is the official implementation of [A Mathematical Framework for Quantifying Transferability in Multi-source Transfer Learning]. 


## Requirements
Python 3.X & Torch 1.7.0


##
In the folder “./data”, we provide the features we used. Folder “o31_feature” contains the features of Office-31 dataset, and folder “oc_feature” contains the features of Office-Caltech dataset. 

## Codes
“cifar10_alpha.py” is an example for CIFAR-10 dataset for the case of 6 target samples. “o31_atod_renew.py” is an example for Office-31 dataset for the case of task A→D, with the details of computing renewed α. “oc_atoc.py” is an example for Office-Caltech dataset for the case of task A→C.
