Ye Yuan

Orcid: 0000-0002-1274-2285

Affiliations:
  • Chinese Academy of Sciences, Institute of Green and Intelligent Technology, Chongqing, China


According to our database1, Ye Yuan authored at least 24 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Pseudo Gradient-Adjusted Particle Swarm Optimization for Accurate Adaptive Latent Factor Analysis.
IEEE Trans. Syst. Man Cybern. Syst., April, 2024

Adaptive Divergence-Based Non-Negative Latent Factor Analysis of High-Dimensional and Incomplete Matrices From Industrial Applications.
IEEE Trans. Emerg. Top. Comput. Intell., April, 2024

An ADRC-Incorporated Stochastic Gradient Descent Algorithm for Latent Factor Analysis.
CoRR, 2024

2023
An Adaptive Divergence-Based Non-Negative Latent Factor Model.
IEEE Trans. Syst. Man Cybern. Syst., October, 2023

A Kalman-Filter-Incorporated Latent Factor Analysis Model for Temporally Dynamic Sparse Data.
IEEE Trans. Cybern., September, 2023

An Adaptive PID-Incorporated Non-Negative Latent Factor Analysis Model.
Proceedings of the IEEE International Conference on Data Mining, 2023

2022
An α-β-Divergence-Generalized Recommender for Highly Accurate Predictions of Missing User Preferences.
IEEE Trans. Cybern., 2022

A Multilayered-and-Randomized Latent Factor Model for High-Dimensional and Sparse Matrices.
IEEE Trans. Big Data, 2022

Graph Regularized Nonnegative Latent Factor Analysis Model for Temporal Link Prediction in Cryptocurrency Transaction Networks.
Proceedings of the IEEE International Conference on Networking, Sensing and Control, 2022

A Nonlinear PID-Enhanced Adaptive Latent Factor Analysis Model.
Proceedings of the IEEE International Conference on Networking, Sensing and Control, 2022

2021
Non-Negative Latent Factor Model Based on β-Divergence for Recommender Systems.
IEEE Trans. Syst. Man Cybern. Syst., 2021

A proportional-integral-derivative-incorporated stochastic gradient descent-based latent factor analysis model.
Neurocomputing, 2021

Dynamic Community Detection via Kalman Filter-Incorporated Non-negative Matrix Factorization.
Proceedings of the IEEE International Conference on Networking, Sensing and Control, 2021

2020
A Generalized and Fast-converging Non-negative Latent Factor Model for Predicting User Preferences in Recommender Systems.
Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

A Nonlinear Proportional Integral Derivative-Incorporated Stochastic Gradient Descent-based Latent Factor Model.
Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics, 2020

Accelerated Latent Factor Analysis for Recommender Systems via PID Controller.
Proceedings of the IEEE International Conference on Networking, Sensing and Control, 2020

Adaptive Regularization-Incorporated Latent Factor Analysis.
Proceedings of the 2020 IEEE International Conference on Knowledge Graph, 2020

Temporal Web Service QoS Prediction via Kalman Filter-Incorporated Latent Factor Analysis.
Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

2019
Randomized latent factor model for high-dimensional and sparse matrices from industrial applications.
IEEE CAA J. Autom. Sinica, 2019

2018
A Highly Accurate Framework for Self-Labeled Semisupervised Classification in Industrial Applications.
IEEE Trans. Ind. Informatics, 2018

Effects of preprocessing and training biases in latent factor models for recommender systems.
Neurocomputing, 2018

Performance of nonnegative latent factor models with β-distance functions in recommender systems.
Proceedings of the 15th IEEE International Conference on Networking, Sensing and Control, 2018

2017
Performance of latent factor models with extended linear biases.
Knowl. Based Syst., 2017

Effect of linear biases in latent factor models on high-dimensional and sparse matrices from recommender systems.
Proceedings of the 14th IEEE International Conference on Networking, Sensing and Control, 2017


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