Efficient Representation to Dynamic QoS Data via Generalized Nesterov's Accelerated Gradient-incorporated Biased Non-negative Latent Factorization of Tensors - researchr publication related

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Minzhi Chen, Xin Luo. Efficient Representation to Dynamic QoS Data via Generalized Nesterov's Accelerated Gradient-incorporated Biased Non-negative Latent Factorization of Tensors. In 2021 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2021, Melbourne, Australia, October 17-20, 2021. pages 576-581, IEEE, 2021. [doi]

The following publications are possibly variants of this publication:

A Generalized Nesterov's Accelerated Gradient-Incorporated Non-Negative Latent-Factorization-of-Tensors Model for Efficient Representation to Dynamic QoS DataMinzhi Chen, Renfang Wang, Yan Qiao, Xin Luo 0001. tetci, 8(3):2386-2400, June 2024. [doi]

A Diverse Biases Non-negative Latent Factorization of Tensors Model for Dynamic Network Link PredictionXuke Wu, Hang Gou, Hao Wu, Juan Wang, Minzhi Chen, Siyu Lai. icnsc 2020: 1-6 [doi]

Momentum-incorporated Latent Factorization of Tensors for Extracting Temporal Patterns from QoS DataMinzhi Chen, Hao Wu, Chunlin He, Sili Chen. SMC 2019: 1757-1762 [doi]

A momentum-incorporated latent factorization of tensors model for temporal-aware QoS missing data predictionQingxian Wang 0001, Minzhi Chen, Mingsheng Shang, Xin Luo 0001. ijon, 367:299-307, 2019. [doi]

Dynamic Network Representation Based on Latent Factorization of TensorsHao Wu, Xuke Wu, Xin Luo. Springer Briefs in Computer Science, Springer, 2023. [doi]

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