Transactions on Machine Learning Research

Aims & Scope

TMLR’s objective is to publish original papers that contribute to the understanding of the computational and mathematical principles that enable intelligence through learning, be it in brains or in machines. To this end, TMLR invites authors to submit papers that contain new algorithms with sound empirical validation, optionally 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 natural learning systems at the behavioral or neural level ; reproducibility studies of previously published results or claims ; new approaches for analysis, visualization, and understanding of artificial or biological learning systems; surveys that draw new connections, highlight trends, and suggest new problems in an area.

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