Abstract:Hard-parameter sharing in multi-domain learning (MDL) allows domains to share some model parameters in order to reduce storage cost while improving prediction accuracy. One traditional paradigm of the sharing practice borrows an idea from multi-task learning (MTL), which is to share bottom layers of a deep neural network among domains while using separate top layers for each domain. However, it is unclear whether the effectiveness of sharing bottom parameters in MTL can transfer to MDL or not. Therefore in thi… Show more
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