Overview
Benelearn 2019, the 28th Belgian Dutch Conference on Machine Learning, is set to take place from November 6 to 8, 2019, in Brussels, Belgium. Organized by the Université Libre de Bruxelles and the Vrije Universiteit Brussel, this event is under the auspices of the Benelux Association for Artificial Intelligence (BNVKI). This year’s conference promises a rich program featuring invited speakers, research presentations, and interactive sessions, making it a significant gathering for the AI and machine learning community.
Background & Relevance
The field of machine learning has rapidly evolved, influencing various domains such as business, healthcare, and technology. Conferences like Benelearn provide a platform for researchers and practitioners to share their findings, discuss innovations, and foster collaborations. The integration of academic and business perspectives at this conference highlights the importance of machine learning applications in real-world scenarios, bridging the gap between theory and practice.
Key Details
- Event Dates: November 6-8, 2019
- Location: Ateliers Des Tanneurs, Brussels, Belgium
- Submission Deadline: August 30, 2019
- Author Notification: September 30, 2019
- Camera Ready Submission Deadline: October 20, 2019
- Topics of Interest: Includes but is not limited to neural networks, reinforcement learning, deep learning, and data mining.
- Submission Link: EasyChair Submission
- Proceedings: Accepted contributions will be included in the online conference proceedings hosted on Ceur.
Eligibility & Participation
Researchers from various backgrounds are encouraged to submit their original work. The conference targets academics, industry professionals, and students interested in machine learning and its applications. There are multiple submission categories to accommodate a range of contributions, from regular papers to thesis abstracts.
Submission or Application Guidelines
Submissions are invited in four categories:
– Type A: Regular papers (10-15 pages for long papers, 6-10 pages for short papers).
– Type B: Compressed contributions (abstracts of previously published work with a 2-page abstract).
– Type C: Demonstrations (2-page abstract with a short video).
– Type D: Thesis abstracts (2-page abstract of completed ML-related theses).
All submissions must adhere to the Springer CCIS/LNCS format and be submitted electronically via EasyChair. Authors must ensure at least one author registers for the conference and presents the paper.
Additional Context / Real-World Relevance
The Benelearn conference serves as a critical venue for discussing advancements in machine learning, a field that is increasingly shaping industries and research landscapes. The collaborative environment fosters innovation and encourages the exchange of ideas, which is essential for the continued growth of AI technologies.
Conclusion
Benelearn 2019 presents an excellent opportunity for researchers and practitioners to engage with the latest developments in machine learning. Interested individuals are encouraged to submit their work and participate in this vibrant academic community. Explore the possibilities, apply, and contribute to the future of machine learning.
Category: CFP & Deadlines
Tags: machine learning, benelearn, bnaic, neural networks, reinforcement learning, deep learning, data mining, predictive modeling
