The FNR is pleased to inform about the Call for the next issue of ERCIM News No. 107 (October 2016). Special theme of this issue is ‘Machine Learning’ – deadline for contributions is Tuesday, 16 August.
- Joint ERCIM Actions
- Special Theme: Machine Learning: The current trends and new paradigms
- Research and Innovation
- In Brief
The Special Theme and the Research and Innovation sections contain articles presenting a panorama of European research activities. The Special Theme focuses on a sector which has been selected by the editors from a short list of currently “hot” topics whereas the Research and Innovation section contains articles describing scientific activities, research results, and technical transfer endeavours in any sector of Information and Communication Science and Technology (ICST), telecommunications or applied mathematics. Submissions to the Special Theme section are subjected to an external review process coordinated by invited guest editors whereas submissions to the Research and Innovation section are checked and approved by the ERCIM News editorial board.
Special Theme: “Machine Learning: The current trends and new paradigms”
- Sander Bohte (CWI, Life Sciences, The Netherlands)
- Hung Son Nguyen (University of Warsaw, Poland)
Machine learning is a methodology to create a mathematical model based on sample data and then use the model to make a prediction or strategy. The machine learning algorithms can be used by computers to learn to see, to understand and to interact with the world around them from collected data and information. With many great successes in recent years, including the triumph of the AlphaGo algorithm developed by Google DeepMind over a professional human player, Machine leaning will seriously impact most industries.
This special theme of ERCIM News will focus on recent topics and advances in machine learning, with particular attention on the current research challenges, the new learning paradigms as well as the most spectacular applications and technologies. Topics include, but are not limited to, the following research areas:
- Deep learning and Deep Neural Networks : recurrent, spiking, probabilistic, etc..
- Distributed Machine Learning: Map Reduce and beyond;
- Machine Learning for Big Data: Real-time, Streaming and Large-Scale algorithms;
- Learning semantics and natural language understanding;
- Supervised, Unsupervised, Reinforcement and Semi-Supervised paradigms;
- Sparse methods: sparse representation & dictionary learning, supervised dictionary learning, etc.
- Hybrid Models using Machine Learning;
- Interdisciplinary Application of Machine Learning;
- Humanoids Behavior and Nature-inspired Machine Learning;
- Advances in research and development of ML Techniques, e.g. Conditional Random Fields, Bayesian Belief Networks, Kernel Methods, etc.
Articles submitted to the special theme are subject to a review process.
Guidelines for ERCIM News articles
Style: ERCIM News is read by a large variety of people. Keeping this in mind the article should be descriptive (emphasize more the ‘what’ than the ‘how’) without too much technical detail together with an illustration, if possible.
Contributions in ERCIM News are normally presented without formulas. One can get a long way with careful phrasing, although it is not always wise to avoid formulas altogether. In cases where authors feel that the use of formulas is necessary to clarify matters, this should be done in a separate box (to be treated as an illustration). However, formulas and symbols scattered through the text must be avoided as much as possible.
Length: Keep the article short, i.e. 700-800 words.
Format: Submissions preferably in ASCII text or MS Word. Pictures/Illustrations must be submitted as separate files (not embedded in a MS Word file) in a resolution/quality suitable for printing.
How to submit
- Articles have to be sent to the local editor for your country (see About ERCIM News) or to the central editor firstname.lastname@example.org
- The local editor for Luxembourg is Thomas Tamisier at the Luxembourg Institute of Science and Technology (LIST)
Benefits of contributing to ERCIM News
Publishing in ERCIM News offers several advantages:
- ERCIM News represents an excellent opportunity to present your research to a broad audience, also outside your own research community
- the printed edition has a circulation of about 5000 copies
- more than 7500 readers are subscribed to the online edition
- ERCIM News is widely distributed in the European Commission
- ERCIM offers a free professional proof-reading service
- Authors can reuse their articles; the copyright of the articles remains with the authors.
- Articles of the sections “Special Theme” and “Research and Innovation” are referenced by DBLP