ERCIM News No. 107 (October 2016)
DEADLINE FOR CONTRIBUTIONS: Tuesday 16 August 2016
Please read the guidelines below before submitting an article
The sections of ERCIM News 107 are :
- Joint ERCIM Actions
- Special Theme: Machine Learning: 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: 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 Behaviour 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.
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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
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