AI RESEARCH
Accelerating Matrix Factorization by Dynamic Pruning for Fast Recommendation
arXiv CS.LG
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ArXi:2404.04265v2 Announce Type: replace-cross Matrix factorization (MF) is a widely used collaborative filtering (CF) algorithm for recommendation systems (RSs), due to its high prediction accuracy, great flexibility and high efficiency in big data processing. However, with the dramatically increased number of users/items in current RSs, the computational complexity for