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ORCIDCe Ju
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2020 – today
- 2024
[c7]Ce Ju, Reinmar J. Kobler, Liyao Tang, Cuntai Guan, Motoaki Kawanabe:
Deep Geodesic Canonical Correlation Analysis for Covariance-Based Neuroimaging Data. ICLR 2024- 2023
- [j1]Ce Ju
, Cuntai Guan:
Tensor-CSPNet: A Novel Geometric Deep Learning Framework for Motor Imagery Classification. IEEE Trans. Neural Networks Learn. Syst. 34(12): 10955-10969 (2023) - [c6]Ce Ju, Reinmar Josef Kobler, Cuntai Guan:
Score-Based Data Generation for EEG Spatial Covariance Matrices: Towards Boosting BCI Performance. EMBC 2023: 1-7 - 2022
- [i14]Ce Ju, Cuntai Guan:
Deep Optimal Transport on SPD Manifolds for Domain Adaptation. CoRR abs/2201.05745 (2022) - [i13]Ce Ju, Cuntai Guan:
Tensor-CSPNet: A Novel Geometric Deep Learning Framework for Motor Imagery Classification. CoRR abs/2202.02472 (2022) - [i12]Ce Ju, Cuntai Guan:
Graph Neural Networks on SPD Manifolds for Motor Imagery Classification: A Perspective from the Time-Frequency Analysis. CoRR abs/2211.02641 (2022) - 2021
- [i11]Chang Liu, Lixin Fan, Kam Woh Ng, Yilun Jin, Ce Ju, Tianyu Zhang, Chee Seng Chan, Qiang Yang:
Ternary Hashing. CoRR abs/2103.09173 (2021) - 2020
- [c5]Ce Ju, Dashan Gao, Ravikiran Mane, Ben Tan, Yang Liu, Cuntai Guan:
Federated Transfer Learning for EEG Signal Classification. EMBC 2020: 3040-3045 - [c4]Lixin Fan, Kam Woh Ng, Ce Ju, Tianyu Zhang, Chee Seng Chan:
Deep Polarized Network for Supervised Learning of Accurate Binary Hashing Codes. IJCAI 2020: 825-831 - [c3]Ce Ju, Zheng Wang, Cheng Long, Xiaoyu Zhang, Dong Eui Chang:
Interaction-aware Kalman Neural Networks for Trajectory Prediction. IV 2020: 1793-1800 - [p1]Lixin Fan, Kam Woh Ng, Ce Ju, Tianyu Zhang, Chang Liu, Chee Seng Chan, Qiang Yang:
Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks. Federated Learning 2020: 32-50 - [i10]Ce Ju, Dashan Gao, Ravikiran Mane, Ben Tan, Yang Liu, Cuntai Guan:
Federated Transfer Learning for EEG Signal Classification. CoRR abs/2004.12321 (2020) - [i9]Ce Ju, Ruihui Zhao, Jichao Sun, Xiguang Wei, Bo Zhao, Yang Liu, Hongshan Li, Tianjian Chen, Xinwei Zhang, Dashan Gao, Ben Tan, Han Yu, Yuan Jin:
Privacy-Preserving Technology to Help Millions of People: Federated Prediction Model for Stroke Prevention. CoRR abs/2006.10517 (2020) - [i8]Lixin Fan, Kam Woh Ng, Ce Ju, Tianyu Zhang, Chang Liu, Chee Seng Chan, Qiang Yang:
Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks. CoRR abs/2006.11601 (2020) - [i7]Dashan Gao, Ben Tan, Ce Ju, Vincent W. Zheng, Qiang Yang:
Privacy Threats Against Federated Matrix Factorization. CoRR abs/2007.01587 (2020) - [i6]Ce Ju:
Geometric Foundations of Data Reduction. CoRR abs/2008.06853 (2020) - [i5]Yilun Jin, Lixin Fan, Kam Woh Ng, Ce Ju, Qiang Yang:
Rethinking Uncertainty in Deep Learning: Whether and How it Improves Robustness. CoRR abs/2011.13538 (2020)
2010 – 2019
- 2019
- [c2]Dashan Gao, Yang Liu, Anbu Huang, Ce Ju, Han Yu, Qiang Yang:
Privacy-preserving Heterogeneous Federated Transfer Learning. IEEE BigData 2019: 2552-2559 - [c1]Zheng Wang, Cheng Long, Gao Cong, Ce Ju:
Effective and Efficient Sports Play Retrieval with Deep Representation Learning. KDD 2019: 499-509 - [i4]Ce Ju, Zheng Wang, Cheng Long, Xiaoyu Zhang, Gao Cong, Dong Eui Chang:
Interaction-aware Kalman Neural Networks for Trajectory Prediction. CoRR abs/1902.10928 (2019) - [i3]Ce Ju, Dong Eui Chang:
Stochastic Inverse Reinforcement Learning. CoRR abs/1905.08513 (2019) - [i2]Dashan Gao, Ce Ju, Xiguang Wei, Yang Liu, Tianjian Chen, Qiang Yang:
HHHFL: Hierarchical Heterogeneous Horizontal Federated Learning for Electroencephalography. CoRR abs/1909.05784 (2019) - 2018
- [i1]Zheng Wang, Ce Ju, Gao Cong, Cheng Long:
Representation Learning for Spatial Graphs. CoRR abs/1812.06668 (2018)
Coauthor Index
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last updated on 2024-10-24 21:33 CEST by the dblp team
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