Distributed Matrix Factorization

Distributed Alternating Least Squares (ALS)

Parallelized matrix factorization algorithm that solves the least squares problem alternately for one of the matrix factors while keeping the other fixed, naturally adapting to distributed environments like Spark MLlib due to the independence of computations on each row or column.

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