Hao Li
Orcid: 0000-0003-2989-0679Affiliations:
- Hunan University, School of Information Science and Engineering, National Supercomputing Center in Changsha, China
According to our database1,
Hao Li
authored at least 13 papers
between 2017 and 2022.
Collaborative distances:
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Bibliography
2022
Multiple Strategies Differential Privacy on Sparse Tensor Factorization for Network Traffic Analysis in 5G.
IEEE Trans. Ind. Informatics, 2022
An Online and Scalable Model for Generalized Sparse Nonnegative Matrix Factorization in Industrial Applications on Multi-GPU.
IEEE Trans. Ind. Informatics, 2022
2021
SGD$\_$_Tucker: A Novel Stochastic Optimization Strategy for Parallel Sparse Tucker Decomposition.
IEEE Trans. Parallel Distributed Syst., 2021
Locality Sensitive Hash Aggregated Nonlinear Neighborhood Matrix Factorization for Online Sparse Big Data Analysis.
Trans. Data Sci., 2021
Locality Sensitive Hash Aggregated Nonlinear Neighbourhood Matrix Factorization for Online Sparse Big Data Analysis.
CoRR, 2021
2020
An online and generalized non-negativity constrained model for large-scale sparse tensor estimation on multi-GPU.
Neurocomputing, 2020
SGD_Tucker: A Novel Stochastic Optimization Strategy for Parallel Sparse Tucker Decomposition.
CoRR, 2020
2019
An efficient manifold regularized sparse non-negative matrix factorization model for large-scale recommender systems on GPUs.
Inf. Sci., 2019
IEEE Access, 2019
2018
MSGD: A Novel Matrix Factorization Approach for Large-Scale Collaborative Filtering Recommender Systems on GPUs.
IEEE Trans. Parallel Distributed Syst., 2018
CUSNTF: A Scalable Sparse Non-negative Tensor Factorization Model for Large-scale Industrial Applications on Multi-GPU.
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018
2017
CuSNMF: A Sparse Non-Negative Matrix Factorization Approach for Large-Scale Collaborative Filtering Recommender Systems on Multi-GPU.
Proceedings of the 2017 IEEE International Symposium on Parallel and Distributed Processing with Applications and 2017 IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC), 2017
An Efficient Parallelization Approach for Large-Scale Sparse Non-Negative Matrix Factorization Using Kullback-Leibler Divergence on Multi-GPU.
Proceedings of the 2017 IEEE International Symposium on Parallel and Distributed Processing with Applications and 2017 IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC), 2017