Stealth cyber-attacks against power grids, water systems and other critical infrastructure often go undetected until it is ...

In the last decade, auxiliary information has been widely used to address data sparsity. Due to the advantages of feature extraction and the no-label requirement, autoencoder-based methods addressing ...

Dr. James McCaffrey from Microsoft Research presents a complete program that uses the Python language LightGBM system to create a custom autoencoder for data anomaly detection. You can easily adapt ...

Apple has published three interesting studies that offer some insight into how AI can improve workflows, quality, and productivity for developers.

New papers on Apple's machine learning blog detail how AI can be used for faster, cheaper, and more effective QE testing, as ...

Cintas, Celia, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan, and Edward McFowland III. "Detecting Adversarial Attacks ...

Chiranjeevi Devi's research focuses on building reliable data systems through anomaly detection, DevSecOps automation, and policy-as-code for compliance.

Recent advances in feature selection methods for breast cancer recurrence prediction: A systematic review. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does not ...