A Parallelized, Momentum-incorporated Stochastic Gradient Descent Scheme for Latent Factor Analysis on High-dimensional and Sparse Matrices from Recommender Systems

2019 IEEE International Conference on Systems, Man and Cybernetics (SMC) ◽

10.1109/smc.2019.8914671 ◽

2019 ◽

Author(s):

Wen Qin ◽

Hao Wu ◽

Qingkuan Lai ◽

Chaobin Wang

Keyword(s):

Factor Analysis ◽

Recommender Systems ◽

Gradient Descent ◽

Sparse Matrices ◽

Stochastic Gradient ◽

Stochastic Gradient Descent ◽

High Dimensional ◽

Latent Factor

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Large-scale and Scalable Latent Factor Analysis via Distributed Alternative Stochastic Gradient Descent for Recommender Systems

IEEE Transactions on Big Data ◽

10.1109/tbdata.2020.2973141 ◽

2020 ◽

pp. 1-1 ◽

Cited By ~ 4

Author(s):

Xiaoyu Shi ◽

Qiang He ◽

Xin Luo ◽

Yannai Bai ◽

Mingsheng Shang

Keyword(s):

Factor Analysis ◽

Recommender Systems ◽

Gradient Descent ◽

Large Scale ◽

Stochastic Gradient ◽

Stochastic Gradient Descent ◽

Latent Factor

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Adjusted Stochastic Gradient Descent for Latent Factor Analysis

Information Sciences ◽

10.1016/j.ins.2021.12.065 ◽

2021 ◽

Author(s):

Qing Li ◽

Diwen Xiong ◽

Mingsheng Shang

Keyword(s):

Factor Analysis ◽

Gradient Descent ◽

Stochastic Gradient ◽

Stochastic Gradient Descent ◽

Latent Factor

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Adaptive Alternating Stochastic Gradient Descent Algorithms for Large-Scale Latent Factor Analysis

10.1109/scc53864.2021.00041 ◽

2021 ◽

Author(s):

Wen Qin ◽

Xin Luo ◽

MengChu Zhou

Keyword(s):

Factor Analysis ◽

Gradient Descent ◽

Large Scale ◽

Stochastic Gradient ◽

Stochastic Gradient Descent ◽

Latent Factor ◽

Descent Algorithms

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Effects of Extended Stochastic Gradient Descent Algorithms on Improving Latent Factor-Based Recommender Systems

IEEE Robotics and Automation Letters ◽

10.1109/lra.2019.2891986 ◽

2019 ◽

Vol 4 (2) ◽

pp. 618-624 ◽

Cited By ~ 1

Author(s):

Xin Luo ◽

MengChu Zhou

Keyword(s):

Recommender Systems ◽

Gradient Descent ◽

Stochastic Gradient ◽

Stochastic Gradient Descent ◽

Latent Factor ◽

Descent Algorithms

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A proportional-integral-derivative-incorporated stochastic gradient descent-based latent factor analysis model

Neurocomputing ◽

10.1016/j.neucom.2020.11.029 ◽

2021 ◽

Vol 427 ◽

pp. 29-39

Author(s):

Jinli Li ◽

Ye Yuan ◽

Tao Ruan ◽

Jia Chen ◽

Xin Luo

Keyword(s):

Factor Analysis ◽

Gradient Descent ◽

Stochastic Gradient ◽

Stochastic Gradient Descent ◽

Proportional Integral Derivative ◽

Analysis Model ◽

Latent Factor ◽

Factor Analysis Model ◽

Proportional Integral

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Fast and Accurate Non-negative Latent Factor Analysis on High-dimensional and Sparse Matrices in Recommender Systems

IEEE Transactions on Knowledge and Data Engineering ◽

10.1109/tkde.2021.3125252 ◽

2021 ◽

pp. 1-1

Author(s):

Xin Luo ◽

Yue Zhou ◽

Zhigang Liu ◽

Mengchu Zhou

Keyword(s):

Factor Analysis ◽

Recommender Systems ◽

Sparse Matrices ◽

High Dimensional ◽

Latent Factor

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On Byzantine-Resilient High-Dimensional Stochastic Gradient Descent

2020 IEEE International Symposium on Information Theory (ISIT) ◽

10.1109/isit44484.2020.9174363 ◽

2020 ◽

Author(s):

Deepesh Data ◽

Suhas Diggavi

Keyword(s):

Gradient Descent ◽

Stochastic Gradient ◽

Stochastic Gradient Descent ◽

High Dimensional

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Two Algorithms Under Stochastic Gradient Descent Framework for Recommender Systems

Lecture Notes in Computer Science - Trends and Applications in Knowledge Discovery and Data Mining ◽

10.1007/978-3-319-13186-3_21 ◽

2014 ◽

pp. 219-230

Author(s):

Tian-Hsiang Huang ◽

Vladimir Nikulin

Keyword(s):

Recommender Systems ◽

Gradient Descent ◽

Stochastic Gradient ◽

Stochastic Gradient Descent

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Parallel multiclass stochastic gradient descent algorithms for classifying million images with very-high-dimensional signatures into thousands classes

Vietnam Journal of Computer Science ◽

10.1007/s40595-013-0013-2 ◽

2014 ◽

Vol 1 (2) ◽

pp. 107-115 ◽

Cited By ~ 12

Author(s):

Thanh-Nghi Do

Keyword(s):

Gradient Descent ◽

Stochastic Gradient ◽

Stochastic Gradient Descent ◽

High Dimensional ◽

Descent Algorithms ◽

Very High

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A Momentum-incorporated Fast Parallelized Stochastic Gradient Descent for Latent Factor Model in Shared Memory Systems

2020 IEEE International Conference on Networking, Sensing and Control (ICNSC) ◽

10.1109/icnsc48988.2020.9238077 ◽

2020 ◽

Author(s):

Hang Gou ◽

Jinli Li ◽

Wen Qin ◽

Chunlin He ◽

Yurong Zhong ◽

...

Keyword(s):

Shared Memory ◽

Gradient Descent ◽

Factor Model ◽

Memory Systems ◽

Stochastic Gradient ◽

Stochastic Gradient Descent ◽

Latent Factor ◽

Latent Factor Model

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