An Adaptive PID-Incorporated Non-Negative Latent Factor Analysis Model-Reference-Cited by-同舟云学术

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An Adaptive PID-Incorporated Non-Negative Latent Factor Analysis Model

Published:2023-12-04 Issue: Volume:17 Page:424-428
ISSN:
Container-title:2023 IEEE International Conference on Data Mining Workshops (ICDMW)
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Author:

Li Jinli¹,Zhou ChengXuan²,Yuan Ye³

Affiliation:

1. Chongqing University of Posts and Telecommunications Chongqing,School of Computer Science and Technology,China,400065

2. School of Computer Science Fudan University,Shanghai,China,200433

3. College of Computer and Information Science Southwest University,Chongqing,China,400715

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10411504/10411508/10411637.pdf?arnumber=10411637

Reference24 articles.

1. Hyperspectral Unmixing Using Higher-Order Graph Regularized NMF With Adaptive Feature Selection

2. Unraveling Metric Vector Spaces With Factorization for Recommendation

3. Non-Negative Latent Factor Model Based on β-Divergence for Recommender Systems

4. Adaptive neuro-fuzzy PID controller based on twin delayed deep deterministic policy gradient algorithm

5. Efficient Extraction of Non-negative Latent Factors from High-Dimensional and Sparse Matrices in Industrial Applications

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