SGD Matrix Factorization Algorithm: Difference between revisions
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An [[SGD Matrix Factorization Algorithm]] is a [[matrix factorization algorithm]] that ... | An [[SGD Matrix Factorization Algorithm]] is a [[matrix factorization algorithm]] that ... | ||
* <B>Example(s):</B> | |||
** ([[Oh et al., 2015]]) | |||
* <B>Counter-Example(s):</B> | * <B>Counter-Example(s):</B> | ||
** [[ALS Matrix Factorization Algorithm]]. | ** [[ALS Matrix Factorization Algorithm]]. | ||
Revision as of 20:33, 24 June 2018
An SGD Matrix Factorization Algorithm is a matrix factorization algorithm that ...
- Example(s):
- Counter-Example(s):
- See: SGD Matrix Factorization System.
References =
2015
- (Oh et al., 2015) ⇒ [[::Jinoh Oh]], [[::Wook-Shin Han]], [[::Hwanjo Yu]], and [[::Xiaoqian Jiang]]. ([[::2015]]). “Fast and Robust Parallel SGD Matrix Factorization." In: [[::Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining]] (KDD-2015). ISBN:978-1-4503-3664-2 doi:10.1145/2783258.2783322
- QUOTE: ... Matrix factorization is known to be an effective method for recommender systems that are given only the ratings from users to items. Currently, stochastic gradient descent (SGD) is one of the most popular algorithms for matrix factorization. However, as a sequential …