Editorial Aims and Scope

Editorial Aims

The growth in all aspects of research has led to a multitude of new publications and an exponential increase in published research. Finding a way through the excellent existing literature and keeping up to date has become a time-consuming problem. Researchers have instant access to more articles than ever before. But which articles are the essential ones that should be read to understand and keep abreast with developments of any topic? To address this problem Foundations and Trends® in Machine Learning publishes high-quality short monographs that provide a starting point for a graduate student or researcher new to a particular topic.

Each issue of Foundations and Trends® in Machine Learning comprises a monograph of at least 50 pages written by research leaders in the field. We aim to publish monographs that provide an in-depth, self-contained treatment of topics where there have been significant new developments. Typically, this means that the monographs we publish will contain a significant level of mathematical detail (to describe the central methods and/or theory for the topic at hand), and will not eschew these details by simply pointing to existing references. Literature surveys and original research papers do not fall within these aims.

Editorial Scope

Foundations and Trends® welcomes monographs that touch on fundamental problems in machine learning from theoretical, methodological, and/or computational perspectives. We are particularly interested in monographs that seek to bridge such problems and perspectives with those from related fields, including (but not limited to) statistics, economics, and optimization.