Ce Ju

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Rethinking Uncertainty in Deep Learning: Whether and How it Improves Robustness

Deep neural networks (DNNs) are known to be prone to adversarial attacks...
11/27/2020 ∙ by Yilun Jin, et al. ∙ 0 ∙ share

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Geometric Foundations of Data Reduction

The purpose of this paper is to write a complete survey of the (spectral...
08/16/2020 ∙ by Ce Ju, et al. ∙ 0 ∙ share

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Privacy Threats Against Federated Matrix Factorization

Matrix Factorization has been very successful in practical recommendatio...
07/03/2020 ∙ by Dashan Gao, et al. ∙ 7 ∙ share

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Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks

This paper investigates capabilities of Privacy-Preserving Deep Learning...
06/20/2020 ∙ by Lixin Fan, et al. ∙ 19 ∙ share

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Privacy-Preserving Technology to Help Millions of People: Federated Prediction Model for Stroke Prevention

prevention of stroke with its associated risk factors has been one of th...
06/15/2020 ∙ by Ce Ju, et al. ∙ 0 ∙ share

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Federated Transfer Learning for EEG Signal Classification

The success of deep learning (DL) methods in the Brain-Computer Interfac...
04/26/2020 ∙ by Ce Ju, et al. ∙ 0 ∙ share

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HHHFL: Hierarchical Heterogeneous Horizontal Federated Learning for Electroencephalography

Electroencephalography (EEG) classification techniques have been widely ...
09/11/2019 ∙ by Dashan Gao, et al. ∙ 0 ∙ share

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Stochastic Inverse Reinforcement Learning

Inverse reinforcement learning (IRL) is an ill-posed inverse problem sin...
05/21/2019 ∙ by Ce Ju, et al. ∙ 0 ∙ share

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Interaction-aware Kalman Neural Networks for Trajectory Prediction

Forecasting the motion of surrounding dynamic obstacles (vehicles, bicyc...
02/28/2019 ∙ by Ce Ju, et al. ∙ 0 ∙ share

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Representation Learning for Spatial Graphs

Recently, the topic of graph representation learning has received plenty...
12/17/2018 ∙ by Zheng Wang, et al. ∙ 0 ∙ share

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Socially Aware Kalman Neural Networks for Trajectory Prediction

Trajectory prediction is a critical technique in the navigation of robot...
09/14/2018 ∙ by Ce Ju, et al. ∙ 0 ∙ share

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Ce Ju

Featured Co-authors

Yang Liu

Chang Liu

Zheng Wang

Qiang Yang

Bo Zhao

Han Yu

Chee Seng Chan

Tianjian Chen

Lixin Fan

Xiaoyu Zhang

Dashan Gao

Rethinking Uncertainty in Deep Learning: Whether and How it Improves Robustness

Geometric Foundations of Data Reduction

Privacy Threats Against Federated Matrix Factorization

Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks

Privacy-Preserving Technology to Help Millions of People: Federated Prediction Model for Stroke Prevention

Federated Transfer Learning for EEG Signal Classification

HHHFL: Hierarchical Heterogeneous Horizontal Federated Learning for Electroencephalography

Stochastic Inverse Reinforcement Learning

Interaction-aware Kalman Neural Networks for Trajectory Prediction

Representation Learning for Spatial Graphs

Socially Aware Kalman Neural Networks for Trajectory Prediction