Defensive Machine Learning Techniques for Countering Adversarial Attacks

The Evaluation of Distance Metrics for Generating Adversarial Perturbations from Univariate Time Series Data

Synthetic Trajectory Generation via Clustering-Based Semi-supervised Generative Adversarial Networks

Towards the Robustness of Deep Learning Systems Against Adversarial Examples in Sequential Data

Mining User Generated Content: Addressing Data Scarcity in Filtering Tasks

Deep Learning with Differential Privacy and Adversarial Robustness

Temporal Irregular Tensor Factorization and Prediction for Health Data Analysis

Differentially Private Deep Learning

Robust Crowdsourcing and Federated Learning under Poisoning Attacks