Machine Learning is an international forum for research on computational approaches to learning. The journal publishes articles reporting substantive results on a wide range of learning methods applied to a variety of learning problems. The journal features papers that describe research on problems and methods, applications research, and issues of research methodology. Papers making claims about learning problems or methods provide solid support via empirical studies, theoretical analysis, or comparison to psychological phenomena. Applications papers show how to apply learning methods to solve important applications problems.
Open Access raises practical and policy questions for scholars, publishers, funders, and policymakers alike, including what the return on investment is when paying an article processing fee to publish in an Open Access articles, or whether investments into institutional repositories should be made and whether self-archiving should be made mandatory, as contemplated by some funders.
Last date updated on July, 2020