Call for papers:
We welcome contributions on both theory and applications related to constructive machine-learning problems (cf our overview). We also welcome submissions containing previously published content in fields related to machine learning, especially descriptions of real-world problems and applications. We welcome work-in-progress contributions, demo and position papers, as well as papers discussing potential research directions. Submission of previously published work or work under review is allowed. However, preference will be given to novel work or work that was not yet presented elsewhere. All double submissions must be clearly declared as such!
Submissions will be reviewed on the basis of relevance, significance, technical quality, and clarity. All accepted papers will be presented as posters and among them a few will be selected for the oral presentation.
Submissions should use the NIPS style file, with a maximum of 4 pages (excluding references). Accepted papers will be made available online at the workshop website, but the workshop proceedings can be considered non-archival. Submissions need not be anonymous. All papers should be submitted via easychair.