Memory-efficient Embedding for Recommendations

26 Jun 2020Xiangyu ZhaoHaochen LiuHui LiuJiliang TangWeiwei GuoJun ShiSida WangHuiji GaoBo Long

Practical large-scale recommender systems usually contain thousands of feature fields from users, items, contextual information, and their interactions. Most of them empirically allocate a unified dimension to all feature fields, which is memory inefficient... (read more)

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