Studies reported that if teachers can accurately predict students' follow-up learning effects
via data mining and other means, as per their current performances, and explore the …

Deep learning networks generally use non-biological learning methods. By contrast,
networks based on more biologically plausible learning, such as Hebbian learning, show …

Recent work on sample efficient training of Deep Neural Networks (DNNs) proposed a semi-
supervised methodology based on biologically inspired Hebbian learning, combined with …

Due to industrial demands to handle increasing amounts of training data, lower the cost of
computing one model at a time, and lessen the ecological effects of intensive computing …

Given the unprecedented growth of deep learning applications, training acceleration is
becoming a subject of strong academic interest. Hebbian learning as a training strategy …

Neural network training requires a lot of resources, and there are situations where training
time and memory usage are limited. In such instances, the undertaking of devising …

Current commonly used image recognition convolutional neural networks share some
similarities with the human brain. However, the differences are many and the well …