The International Journal of Machine Learning (IJOML) provides a global forum for disseminating high-quality, peer-reviewed research on theoretical foundations, methodological innovations, and applied advancements in machine learning. The journal emphasizes transparency, reproducibility, and accessibility of data, algorithms, and processes to foster accountable and impactful scientific progress. IJOML welcomes original contributions, surveys, and case studies that enhance the understanding and application of machine learning in both academic and industrial contexts. The journal is published twice a year, in June and December.