Power distribution systems are often conceptualized as optimization models. While optimizing agents to perform tasks works well for systems with limited checkpoints, things begin to go out of hand ...

Collaborative learning has been widely used in both offline and online contexts to support deep learning, and its effectiveness may be adjusted by the size of the collaborative groups. To examine the ...

This report explores the problem of training a Deep Learning (DL) model to recognise and classify 10 different types of foods sampled from the Food-101 dataset to satisfactory level of accuracy. It ...

Many instructors approach assignment design with a "product" focus—that is to say, the choices they make about their assignments (frequency; genre; difficulty; grading scheme; etc.) are oriented ...

Reinforcement Learning (RL) is a critical area of ML that allows agents to learn from their interactions within an environment by receiving feedback as rewards. A significant challenge in RL is ...