作者:bestrivern 

一.迁移学习(Transfer learning)

1.Task A and Task B has the same input x

2.You have a lot more data for Task A than Task B

3.Low level features from A could be helpful for learning B


 (感觉上面的第一点说的好像不太对, 所以 ,ps: point 1 is conflict with point 2, maybe point 1 should be  task A has input x  and   task B has input y,   input x  is similar with input y)

二.多任务学习(Multitask learning)

1.Training on a set of tasks that could benefit from having shared low-level features

2.Usually:Amount of data you have for each task is quite similar

3.Can train a big enough neural network to do well on all the tasks

三.端到端学习(End-to-end deep learning)

Pros:

Let the data speak

Less hand-designing of components needed

Cons: 

May need large amount of data

Excludes potentially useful hand-designed components


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