92 citations · 101 across the 4 of their papers we have counts for
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cs.LG2021★ 1 cited
iALS++: Speeding up Matrix Factorization with Subspace Optimization
Steffen Rendle, Walid Krichene, Li Zhang +1
iALS is a popular algorithm for learning matrix factorization models from implicit feedback with alternating least squares. This algorithm was invented over a decade ago but still…
cs.IR2021★ 2 cited
Revisiting the Performance of iALS on Item Recommendation Benchmarks
Steffen Rendle, Walid Krichene, Li Zhang +1
Matrix factorization learned by implicit alternating least squares (iALS) is a popular baseline in recommender system research publications. iALS is known to be one of the most com…