The Journal of Machine Learning Research (JMLR) provides an international forum for the electronic and paper publication of high-quality scholarly articles in all areas of machine learning. All published papers are freely available online. 

JMLR seeks previously unpublished papers on machine learning that contain:

    new principled algorithms with sound empirical validation, and with justification of theoretical, psychological, or biological nature;
    experimental and/or theoretical studies yielding new insight into the design and behavior of learning in intelligent systems;
    accounts of applications of existing techniques that shed light on the strengths and weaknesses of the methods;
    formalization of new learning tasks (e.g., in the context of new applications) and of methods for assessing performance on those tasks;
    development of new analytical frameworks that advance theoretical studies of practical learning methods;
    computational models of data from natural learning systems at the behavioral or neural level; or
    extremely well-written surveys of existing work.