Benelearn 2017:
The annual machine learning conference of Belgium and The Netherlands
Eindhoven (Netherlands), 9-10 June 2017




Deep Learning methods have shown significant success in takling some of the major long-standing challenges in Machine Learning. Particular applications to Image Analysis, Speech Recognition, Natural Language Processing and many others demonstrate the important advances in this field. This has generated particular attention to Deep Learning, but also to the Machine Learning field in general. To host a more focused discussion, we have created as special track on Deep Learning as part of Benelearn 2017.

Relevant topics:

We are looking for contributions focusing on Neural Network models towards the list of (but not limitted to) the following goals:
  • Unsupervised, semi-supervised, and supervised learning
  • Deep Reinforcement learning
  • Generative Models
  • Adveserial Training
  • Efficient and one-shot learning
  • Applications of Deep Neural Network models to vision, audio, speech, natural language processing, robotics, neuroscience, or any other field


March 27, 2017 Submission due (for both full and short papers)
April 25, 2017 Notification of acceptance
May 15, 2017 Camera-ready versions due
June 9-10, 2017 Conference days


The conference solicits regular contributions (5-10 pages) of original work and extended abstracts (2 pages max.) of original work or work that was recently accepted or published in a peer-reviewed machine-learning, data mining or other relevant journal or high level international conference. In the latter case, the publication reference should be clearly mentioned, and the abstracts should be checked mainly for relevance, rather than receive a full review.

We explicitly invite different kinds of contributions, including technical contributions, visionary papers, case studies, demos, benchmark real and synthetic datasets.

The program committee will decide which contributions are selected for an oral presentation, and which ones are presented during a poster session (with spotlight presentations). Preference of authors will be taken into account as well. If your submission falls under one of the special tracks, we encourage you to submit it there.

All submissions must be in English and must be submitted as PDF files through the EasyChair submission page.

Submissions should be formatted using the Benelearn 2017 LaTeX template. For detailed formatting instructions, please refer to the template files. The maximum abstract length is 2 pages (references not included).

All accepted contributions will be published in the conference proceedings and publicly available on the Benelearn website, but no copyright will be claimed.

At least one author of each accepted submission will be expected to attend and present their findings at the conference. The deadline for paper submission is March 27, 2017.

Submissions are invited in several categories, including but not limited to:

  • Technical contributions,
  • Vision papers, emphasizing controversial and emerging topics, and
  • System demonstrations (e.g., software or benchmarks).
We impose no hard page length requirements. Submissions can be shorter papers (extended abstracts or short reports, for which the recommended length is two to four pages) or longer reports (recommeded length: six to eight pages). All papers should be prepared in PDF, using ACM SIG format.

All submissions will be reviewed by the Program Committee based on technical quality, relevance, originality, significance, and clarity. All papers should be submitted through the EasyChair Submission Site. During the submission process, please indicate the intended type of the manuscript to assist the program committee with their assessment (e.g., an extended abstract of a system demonstration; a report on work in progress; a vision paper).

All accepted workshop papers will be published in an informal proceedings (or Arxiv). Our intention is to organize a special issue on Evolving Networks Analytics (e.g., with ACM SIGKDD Explorations), which would feature reviews of the current state-of-the-art, position papers and regular contributions.


Vlado Menkovski and Eric Postma

For further questions, please contact the organizers at