With the rapid expansion of the new energy vehicle (NEV) market, charging and battery swapping have emerged as the two ...
Abstract: Learning over time for machine learning (ML) models is emerging as a new field, often called continual learning or lifelong Machine learning (LML). Today, deep learning and neural networks ...
Abstract: Random prime number generation is crucial for the implementation of several encryption and signature protocols in cryptographic applications. Recently, Quantum Random Number Generators ...
Tabular data—structured information stored in rows and columns—is at the heart of most real-world machine learning problems, from healthcare records to financial transactions. Over the years, models ...
This project evaluates how effectively static features extracted from Windows Portable Executable (PE) files can distinguish ransomware from benign software using supervised machine learning. This ...