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Qianqian Tong
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引用次数
引用次数
年份
Calibrating the adaptive learning rate to improve convergence of ADAM
Q Tong, G Liang, J Bi
Neurocomputing 481, 333-356, 2022
81*2022
Effective federated adaptive gradient methods with non-iid decentralized data
Q Tong, G Liang, J Bi
arXiv preprint arXiv:2009.06557, 2020
332020
Multi-view spectral graph convolution with consistent edge attention for molecular modeling
C Shang, Q Liu, Q Tong, J Sun, M Song, J Bi
Neurocomputing 445, 12-25, 2021
192021
Federated nonconvex sparse learning
Q Tong, G Liang, T Zhu, J Bi
arXiv preprint arXiv:2101.00052, 2020
122020
Asynchronous parallel stochastic Quasi-Newton methods
Q Tong, G Liang, X Cai, C Zhu, J Bi
Parallel computing 101, 102721, 2021
82021
An effective hard thresholding method based on stochastic variance reduction for nonconvex sparse learning
G Liang, Q Tong, C Zhu, J Bi
Proceedings of the AAAI Conference on Artificial Intelligence 34 (02), 1585-1592, 2020
72020
Federated Optimization of 0-norm Regularized Sparse Learning
Q Tong, G Liang, J Ding, T Zhu, M Pan, J Bi
Algorithms 15 (9), 319, 2022
32022
Escaping saddle points with stochastically controlled stochastic gradient methods
G Liang, Q Tong, C Zhu, J Bi
arXiv preprint arXiv:2103.04413, 2021
32021
Stochastic privacy-preserving methods for nonconvex sparse learning
G Liang, Q Tong, J Ding, M Pan, J Bi
Information Sciences 630, 567-585, 2023
22023
An Effective Tensor Regression with Latent Sparse Regularization.
K Chen, T Xu, G Liang, Q Tong, M Song, J Bi
Journal of Data Science 20 (2), 2022
22022
Stochastic Variance-Reduced Iterative Hard Thresholding in Graph Sparsity Optimization
D Fox, S Hernandez, Q Tong
arXiv preprint arXiv:2407.16968, 2024
2024
Effective Proximal Methods for Non-convex Non-smooth Regularized Learning
G Liang, Q Tong, J Ding, M Pan, J Bi
2020 IEEE International Conference on Data Mining (ICDM), 342-351, 2020
2020
Parallel and Federated Algorithms for Large-scale Machine Learning Problems
Q Tong
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