Soft parameter sharing is the regularization between parameter distance to make the parameters similar. However, in soft parameter sharing each task has its own parameters.

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1) Hard parameter sharing
2) Soft parameter sharing


Two types of Multi task learning methods


Hard parameter sharing is the sharing of the hidden layers while keeping specific layers for each task separate from one another. It reduces overfitting since it tries to find similarities across tasks rather than overfitting the original task.

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