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0111 · Feb 201919922001200920172026
3 results for field-wise

Factorization Machine (FM) is a widely used supervised learning approach by effectively modeling of feature interactions. Despite the successful application of FM and its many deep learning variants, treating every feature interaction fairly may degrade the performance. For example, the interactions of a useless featur…

2019-02-26abs ↗pdf ↗

A new method reduces inference cost for FwFM by allowing it to scale with item fields only.

problem High computational cost in FwFM for large field counts.
method Low-rank diagonal plus symmetric decomposition for field-wise interactions.
result Aggressive rank reduction outperforms pruning in accuracy and speed.