Foundations and Trends in Machine Learning

Foundations and Trends in Machine Learning (FOUND TRENDS MACH LE), ISSN 1935-8237, is a premier peer-reviewed journal published by Now Publishers. As indicated by its exceptional 2026 Impact Factor of 36.600 and its Q1 ranking in the Journal Citation Reports, the journal occupies the very highest tier of scholarly publications in the field. The journal is dedicated to publishing substantial, high-impact survey and review articles that provide a comprehensive and authoritative perspective on critical topics within machine learning. Its scope encompasses the full breadth of the discipline, including but not limited to statistical learning theory, deep learning architectures, reinforcement learning, probabilistic graphical models, optimization algorithms, and the theoretical foundations of learning systems. Unlike journals that prioritize short research papers, Foundations and Trends in Machine Learning focuses exclusively on in-depth, monograph-length reviews that synthesize the state of the art, identify open challenges, and chart future research directions. Each article is written by leading researchers and is designed to serve as a definitive reference for the community. The target audience includes academic researchers, graduate students, and industry professionals who require rigorous, self-contained treatments of advanced topics. A notable feature of the journal is its commitment to open access, ensuring that its influential content is freely and permanently available to a global readership. By consistently publishing work of the highest caliber and impact, the journal has established itself as an indispensable resource and a benchmark for excellence in machine learning scholarship.