Concept learning is important for AI because it can enable the system to acquire and organize knowledge in a meaningful and efficient way. Concept learning can help the system to reduce the ...

It is intended both for newcomers to machine learning and for those already experienced in the field. Covering key concepts relating to contemporary architectures and techniques, this essential book ...

This paper addresses the challenge of learning a local visual pattern of an object from one image, and generating images depicting objects with that pattern. Learning a localized concept and placing ...

Abstract: This book chapter offers a concise overview of key concepts, libraries, and essential tools in machine learning and deep learning. It covers learning styles such as supervised, unsupervised, ...

Concept mapping is a graphic approach to supporting, monitoring, and measuring student learning around a particular concept (Hay, 2007). Concept maps visually represent “a set of concept meanings ...

Seeing how the concept maps grow and develop greater nuance and complexity over time helps students (and the instructor) see what they are learning. Create a fill-in-the-blank concept map in which ...

We propose a novel approach to perform concept-cognitive learning in interval-valued formal contexts from a granular computing viewpoint. This work has been accepted for publication in International ...