BENELEARN 2015 - Belgian-Dutch Conference on Machine Learning (Benelearn)

We solicit submissions for oral or poster presentation at the 24th Belgian-Dutch Conference on Machine Learning (Benelearn), to be held on June 19, 2015 in Delft, The Netherlands. The conference brings together researchers and practitioners from academia and industry to discuss the latest developments in all aspects of machine learning.
The following keynote speakers have agreed to speak at the conference:
- Kilian Weinberger (Washington University in St. Louis)
- Charles Elkan (University of California, San Diego / Amazon)
- Tim Salimans (Algoritmica)
The conference solicits two types of contributions:
- Type A: Type A contributions present new unpublished work in a paper of 4-8 pages. Short discussion or position papers (of about 2 pages) are also welcome. The papers will be peer-reviewed by the program committee. In case of acceptance, Benelearn does not claim copyright of the paper, so you are free to re-submit it elsewhere after Benelearn.
- Type B: Type B contributions are abstracts (2 pages max.) of work that was previously published in another peer-reviewed machine-learning venue (ICML, KDD, JMLR, IEEE TPAMI, etc.). Abstracts will not be peer-reviewed, but are used to determine the final program of the conference.
To ensure a high quality of the conference and to reduce reviewer load, we particularly encourage the submission of type B papers.
All contributions will be published on the Benelearn website, but no copyright will be claimed. The program committee will decide on which (A and B) contributions to selected for an oral presentation, and which ones for a poster presentation. For details on how to submit, please refer to http://www.benelearn2015.nl
Submission deadline: March 27, 2015
Topics that are of interest to the conference include:
- Bayesian Learning
- Case-based Learning
- Causal Learning
- Ensemble Methods
- Computational Learning Theory
- Kernel Methods
- Data Mining
- Inductive Logic Programming
- Knowledge Discovery in Databases
- Online Learning
- Learning in Multi-Agent Systems
- Deep Learning
- Reinforcement Learning
- Robot Learning
- Feature Selection and Dimensionality Reduction
- Scientific Discovery
- Transfer Learning
- Ranking
- Preference Learning
- Information Retrieval
- Computational Models of Human Learning
- Structured Output Learning
- Learning for Language and Speech
- Computer Vision and Text Analytics
- Applications of Machine Learning
This list of topics is non-exhaustive. In case of any doubt about whether your topic is appropriate for presentation at the conference, please contact the program chairs