Ce Ju | DeepAI

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∙ 02/05/2022

Tensor-CSPNet: A Novel Geometric Deep Learning Framework for Motor Imagery Classification

Deep learning (DL) has been widely investigated in a vast majority of ap...

0 Ce Ju, et al. ∙

∙ 01/15/2022

Deep Optimal Transport on SPD Manifolds for Domain Adaptation

The domain adaption (DA) problem on symmetric positive definite (SPD) ma...

0 Ce Ju, et al. ∙

∙ 03/16/2021

Ternary Hashing

This paper proposes a novel ternary hash encoding for learning to hash m...

0 Chang Liu, et al. ∙

∙ 11/27/2020

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

Deep neural networks (DNNs) are known to be prone to adversarial attacks...

0 Yilun Jin, et al. ∙

∙ 08/16/2020

Geometric Foundations of Data Reduction

The purpose of this paper is to write a complete survey of the (spectral...

0 Ce Ju, et al. ∙

∙ 07/03/2020

Privacy Threats Against Federated Matrix Factorization

Matrix Factorization has been very successful in practical recommendatio...

7 Dashan Gao, et al. ∙

∙ 06/20/2020

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

This paper investigates capabilities of Privacy-Preserving Deep Learning...

19 Lixin Fan, et al. ∙

∙ 06/15/2020

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...

0 Ce Ju, et al. ∙

∙ 04/26/2020

Federated Transfer Learning for EEG Signal Classification

The success of deep learning (DL) methods in the Brain-Computer Interfac...

0 Ce Ju, et al. ∙

∙ 09/11/2019

HHHFL: Hierarchical Heterogeneous Horizontal Federated Learning for Electroencephalography

Electroencephalography (EEG) classification techniques have been widely ...

0 Dashan Gao, et al. ∙

∙ 05/21/2019

Stochastic Inverse Reinforcement Learning

Inverse reinforcement learning (IRL) is an ill-posed inverse problem sin...

0 Ce Ju, et al. ∙

∙ 02/28/2019

Interaction-aware Kalman Neural Networks for Trajectory Prediction

Forecasting the motion of surrounding dynamic obstacles (vehicles, bicyc...

0 Ce Ju, et al. ∙

∙ 12/17/2018

Representation Learning for Spatial Graphs

Recently, the topic of graph representation learning has received plenty...

0 Zheng Wang, et al. ∙

∙ 09/14/2018

Socially Aware Kalman Neural Networks for Trajectory Prediction

Trajectory prediction is a critical technique in the navigation of robot...

0 Ce Ju, et al. ∙