Computational Linguistics is the only publication devoted exclusively to the design and analysis of natural language processing systems. From this unique quarterly, university and industry linguists, computational linguists, artificial intelligence (AI) investigators, cognitive scientists, speech specialists, and philosophers get information about computational aspects of research on language, linguistics, and the psychology of language processing and performance.

Computational Linguistics is published by MIT Press and is also available on the MIT Press journals site.

Evolutionary Computation provides an international forum for facilitating and enhancing the exchange of information among researchers involved in both the theoretical and practical aspects of computational systems of an evolutionary nature. The journal publishes both theoretical and practical developments of computational systems drawing their inspiration from nature, with particular emphasis on evolutionary algorithms (EAs), including, but not limited to, genetic algorithms (GAs), evolution strategies (ESs), evolutionary programming (EP), genetic programming (GP), classifier systems (CSs), and other natural computation techniques.

The Journal of Artificial Intelligence Research (www.jair.org) covers all areas of artificial intelligence, publishing refereed research articles, survey articles, and technical notes. JAIR was established in 1993 as one of the very first open access scientific journals on the Web. Since it began publication in 1993, JAIR has had a major impact on the field, and has been continuously ranked as one of the top journals covering AI.

To submit articles and see journal details visit www.jair.org

The Journal of Computing Sciences in Colleges is distributed to faculty in over 200 colleges.

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.

JMLR seeks previously unpublished papers that contain:

• new algorithms with empirical, theoretical, psychological, or biological justification;
• 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.

JMLR has a commitment to rigorous yet rapid reviewing. Final versions are published electronically (ISSN 1533-7928) immediately upon receipt. Printed volumes (ISSN: 1532-4435) are now published by Microtome Publishing and available for sale.

Journal of User Experience (JUX) is a peer-reviewed, international, online publication dedicated to promoting and enhancing the practice, research, and education of user experience (UX) design and evaluation.
The journal aims to provide UX practitioners and researchers with a forum to share:

• Empirical findings and case studies
• Emerging methods and tools from within the user experience profession and from related disciplines, such as market research and technical communications
• Approaches and case studies in UX education and training