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Defensive Machine Learning Techniques for Countering Adversarial Attacks
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The Evaluation of Distance Metrics for Generating Adversarial Perturbations from Univariate Time Series Data
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Synthetic Trajectory Generation via Clustering-Based Semi-supervised Generative Adversarial Networks
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Towards the Robustness of Deep Learning Systems Against Adversarial Examples in Sequential Data
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Mining User Generated Content: Addressing Data Scarcity in Filtering Tasks
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Deep Learning with Differential Privacy and Adversarial Robustness
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Temporal Irregular Tensor Factorization and Prediction for Health Data Analysis
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Differentially Private Deep Learning
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Robust Crowdsourcing and Federated Learning under Poisoning Attacks
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Deep Learning for Skyline Queries
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