
Rethinking Uncertainty in Deep Learning: Whether and How it Improves Robustness
Deep neural networks (DNNs) are known to be prone to adversarial attacks...
read it

Geometric Foundations of Data Reduction
The purpose of this paper is to write a complete survey of the (spectral...
read it

Privacy Threats Against Federated Matrix Factorization
Matrix Factorization has been very successful in practical recommendatio...
read it

Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks
This paper investigates capabilities of PrivacyPreserving Deep Learning...
read it

PrivacyPreserving 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...
read it

Federated Transfer Learning for EEG Signal Classification
The success of deep learning (DL) methods in the BrainComputer Interfac...
read it

HHHFL: Hierarchical Heterogeneous Horizontal Federated Learning for Electroencephalography
Electroencephalography (EEG) classification techniques have been widely ...
read it

Stochastic Inverse Reinforcement Learning
Inverse reinforcement learning (IRL) is an illposed inverse problem sin...
read it

Interactionaware Kalman Neural Networks for Trajectory Prediction
Forecasting the motion of surrounding dynamic obstacles (vehicles, bicyc...
read it

Representation Learning for Spatial Graphs
Recently, the topic of graph representation learning has received plenty...
read it

Socially Aware Kalman Neural Networks for Trajectory Prediction
Trajectory prediction is a critical technique in the navigation of robot...
read it
Ce Ju
is this you? claim profile