Editorial Exploratory research in machine learning

Exploratory research contributes to the continued vitality of every discipline. The aim of exploratory research is to identify new tasks--tasks that cannot be solved by existing methods. Once a new task has been found, exploratory research seeks to develop a precise definition of the task and to understand the factors that make the task different from previously-solved tasks. Until recently, most research in machine learning was primarily exploratory. However, during the past decade, some areas of the field--particularly inductive learning--have matured to the point that careful, quantitative experiments are now possible and proved theoretical results have been obtained. Although these trends are extremely healthy and long overdue, there is a danger that the increased attention to these products of mature research may discourage researchers from undertaking and publishing research of a more exploratory nature. The goal of this editorial is to emphasize the importance of exploratory research and to encourage the publication of high quality exploratory results in Machine Learning.

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