Efficient and High-quality Recommendations via Momentum-incorporated Parallel Stochastic Gradient Descent-Based Learning

doi:10.1109/JAS.2020.1003396

CORC > 自动化研究所 > 中国科学院自动化研究所 > 学术期刊 > IEEE/CAA Journal of Automatica Sinica

	Efficient and High-quality Recommendations via Momentum-incorporated Parallel Stochastic Gradient Descent-Based Learning
	Xin Luo; Wen Qin; Ani Dong; Khaled Sedraoui; MengChu Zhou
刊名	IEEE/CAA Journal of Automatica Sinica
	2021
卷号	8 期号:2 页码:402-411
关键词	Big data industrial application industrial data latent factor analysis machine learning parallel algorithm recommender system (RS) stochastic gradient descent (SGD)
ISSN号	2329-9266
DOI	10.1109/JAS.2020.1003396
英文摘要	A recommender system (RS) relying on latent factor analysis usually adopts stochastic gradient descent (SGD) as its learning algorithm. However, owing to its serial mechanism, an SGD algorithm suffers from low efficiency and scalability when handling large-scale industrial problems. Aiming at addressing this issue, this study proposes a momentum-incorporated parallel stochastic gradient descent (MPSGD) algorithm, whose main idea is two-fold: a) implementing parallelization via a novel data-splitting strategy, and b) accelerating convergence rate by integrating momentum effects into its training process. With it, an MPSGD-based latent factor (MLF) model is achieved, which is capable of performing efficient and high-quality recommendations. Experimental results on four high-dimensional and sparse matrices generated by industrial RS indicate that owing to an MPSGD algorithm, an MLF model outperforms the existing state-of-the-art ones in both computational efficiency and scalability.
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/43920]
专题	自动化研究所_学术期刊_IEEE/CAA Journal of Automatica Sinica
推荐引用方式 GB/T 7714	Xin Luo,Wen Qin,Ani Dong,et al. Efficient and High-quality Recommendations via Momentum-incorporated Parallel Stochastic Gradient Descent-Based Learning[J]. IEEE/CAA Journal of Automatica Sinica,2021,8(2):402-411.
APA	Xin Luo,Wen Qin,Ani Dong,Khaled Sedraoui,&MengChu Zhou.(2021).Efficient and High-quality Recommendations via Momentum-incorporated Parallel Stochastic Gradient Descent-Based Learning.IEEE/CAA Journal of Automatica Sinica,8(2),402-411.
MLA	Xin Luo,et al."Efficient and High-quality Recommendations via Momentum-incorporated Parallel Stochastic Gradient Descent-Based Learning".IEEE/CAA Journal of Automatica Sinica 8.2(2021):402-411.