Aims and Scope

The journal is devoted to providing an open access forum for machine learning research, its applications and practice. It interprets machine learning in its broadest sense covering research in areas such as artificial intelligence, computational intelligence, computer vision, deep learning, multimedia indexing, speech and natural language processing and their applications in all areas of society. The journal places a special emphasis on machine learning practice by soliciting work that takes a systems approach to real-world applications of machine learning and addresses issues such as bias, trust and privacy, performance optimization, and interpretability. Case studies about deploying machine learning in different sectors of the society and tutorials on interdisciplinary topics involving machine learning are welcome.