Hao Wu
Orcid: 0000-0002-4138-1239Affiliations:
- Southwest University, College of Computer and Information Science, Chongqing, China
- Chinese Academy of Sciences, Chongqing Institute of Green and Intelligent Technology, Chongqing, China
- University of Chinese Academy of Sciences, Beijing, China (PhD 2022)
According to our database1,
Hao Wu authored at least 23 papers
between 2020 and 2026.
Collaborative distances:
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Bibliography
2026
A survey of latent factorization of tensor-based model compression: Algorithms, toolboxes and future directions.
Neurocomputing, 2026
Adaptive tucker decomposition-based progressive model compression for convolutional neural networks.
Expert Syst. Appl., 2026
2025
A Convolution Bias-Incorporated Nonnegative Latent Factorization of Tensors Model for Accurate Representation Learning to Dynamic Directed Graphs.
IEEE Trans. Syst. Man Cybern. Syst., December, 2025
Learning Accurate Representation to Nonstandard Tensors via a Mode-Aware Tucker Network.
IEEE Trans. Knowl. Data Eng., December, 2025
A Comprehensive Review of Parallel Optimization Algorithms for High-Dimensional and Incomplete Matrix Factorization.
IEEE CAA J. Autom. Sinica, December, 2025
A Proximal-ADMM-Incorporated Nonnegative Latent-Factorization-of-Tensors Model for Representing Dynamic Cryptocurrency Transaction Network.
IEEE Trans. Syst. Man Cybern. Syst., November, 2025
A Novel Tensor Causal Convolution Network Model for Highly-Accurate Representation to Spatio-Temporal Data.
IEEE Trans Autom. Sci. Eng., 2025
Int. J. Pattern Recognit. Artif. Intell., 2025
A Cauchy loss-incorporated nonnegative latent factorization of tensors model for spatiotemporal traffic data recovery.
Neurocomputing, 2025
An adaptive PID-guided tensor wheel decomposition model for dynamic weighted network representation.
Neurocomputing, 2025
2024
A Fine-Grained Regularization Scheme for Non-negative Latent Factorization of High-Dimensional and Incomplete Tensors.
IEEE Trans. Serv. Comput., 2024
Temporal pattern-aware QoS prediction by Biased Non-negative Tucker Factorization of tensors.
Neurocomputing, 2024
2023
Neulft: A Novel Approach to Nonlinear Canonical Polyadic Decomposition on High-Dimensional Incomplete Tensors.
IEEE Trans. Knowl. Data Eng., June, 2023
Springer Briefs in Computer Science, Springer, ISBN: 978-981-19-8933-9, 2023
Spatio-Temporal Traffic Data Recovery Via Latent Factorization of Tensors Based on Tucker Decomposition.
Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2023
2022
Advancing Non-Negative Latent Factorization of Tensors With Diversified Regularization Schemes.
IEEE Trans. Serv. Comput., 2022
A Novel Approach to Large-Scale Dynamically Weighted Directed Network Representation.
IEEE Trans. Pattern Anal. Mach. Intell., 2022
A PID-incorporated Latent Factorization of Tensors Approach to Dynamically Weighted Directed Network Analysis.
IEEE CAA J. Autom. Sinica, 2022
2021
Adjusting Learning Depth in Nonnegative Latent Factorization of Tensors for Accurately Modeling Temporal Patterns in Dynamic QoS Data.
IEEE Trans Autom. Sci. Eng., 2021
Neural Latent Factorization of Tensors for Dynamically Weighted Directed Networks Analysis.
Proceedings of the 2021 IEEE International Conference on Systems, Man, and Cybernetics, 2021
Instance-Frequency-Weighted Regularized, Nonnegative and Adaptive Latent Factorization of Tensors for Dynamic QoS Analysis.
Proceedings of the 2021 IEEE International Conference on Web Services, 2021
Discovering Hidden Pattern in Large-scale Dynamically Weighted Directed Network via Latent Factorization of Tensors.
Proceedings of the 17th IEEE International Conference on Automation Science and Engineering, 2021
2020
Temporal Pattern-Aware QoS Prediction via Biased Non-Negative Latent Factorization of Tensors.
IEEE Trans. Cybern., 2020