This package demonstrates how to build a transfer learning network effortlessly with Theano and Mozi.

Standard transfer learning also known as multi-task learning or multi-modal learning typically has multiple inputs and multiple outputs. And generally there are two types, Type 1 (Fig 1) has a common shared representation layer where the objective is to map different modalities into a common representation space, while Type 2 (Fig 2) tries to keep individual modality representation space separate, and finally concatenate them to pass through subsequent layers for fine-tuning.

The way to train Type1 and Type2 is also different. For Type 1, you first train 1 -> 3 (Fig 1a) then 2 -> 3 (Fig 1b), while for Type 2, you concatenate the outputs from step 1 and step 2 (Fig 2) before proceeding to step 3 with the concatenated features, i.e 1 + 2 -> 3.

Checkout Type 1 Model and Type 2 Model