CALL FOR ABSTRACTS: BENELEARN 2016 September 12-13, 2016. Kortrijk, Belgium http://www.kuleuven-kulak.be/benelearn/ Benelearn is the annual machine learning conference of Belgium and The Netherlands. It serves as a forum for researchers to exchange ideas, present recent work, and foster collaboration in the broad field of Machine Learning and its applications. The 25th edition will be co-organised by KU Leuven, UGent and the Flemish Supercomputer Centre at the Katholieke Universiteit Leuven, Campus Kortrijk (KULAK). In contrast to previous editions, the anniversary edition of Benelearn will be organised on two days, where the first day will feature a workshop on Big Data, including keynote speakers, a tutorial session, corporate presentations, and ample opportunity for networking. KEYNOTE SPEAKERS: The following keynote speakers have already agreed to speak at the conference: Jeff Ullman (Stanford University) Christian Blum (University of the Basque Country) Hugo Ceulemans (Janssen R&D) Greg Tsoumakas (Aristotle University of Thessaloniki) Emilia Barakova (Technische Universiteit Eindhoven) SUBMISSIONS: The conference solicits abstract contributions (2 pages max.) of original work or work that was recently accepted or published in a peer-reviewed machine-learning journal or at a 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. 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). Submissions related to Big Data analysis will preferably be presented on the thematic day. All accepted contributions will be published on the Benelearn website, but no copyright will be claimed. For submission instructions, please refer tohttp://www.kuleuven-kulak.be/benelearn/. SCOPE: Although we particularly encourage submissions related to learning from Big Data, submissions from all topics of interest within machine learning are welcome (non-exhaustive list): Kernel Methods Bayesian Learning Case-based Learning Causal Learning Ensemble Methods Computational Learning Theory Data Mining Evolutionary Computation Inductive Logic Programming Knowledge Discovery in Databases Online Learning Learning in Multi-Agent Systems Neural Networks Deep Learning Reinforcement Learning Robot Learning Feature Selection and Dimensionality Reduction Scientific Discovery Transfer Learning Statistical Learning Ranking / Preference Learning / Information Retrieval Computational models of Human Learning Structured Output Learning Learning for Language and Speech Media Mining and Text Analytics Learning and Ubiquitous Computing Applications of Machine Learning KEY DATES: Submission deadline: June 1, 2016. Notification of acceptance: July 1, 2016. Conference: September 12-13, 2016. Organizing committee: Celine Vens (KU Leuven) Patrick De Causmaecker (KU Leuven) Yvan Saeys (UGent) Ewald Pauwels (VSC) -- ====================================================================== Prof. dr. Yvan Saeys VIB Group Leader Data mining and modeling for biomedicine Inflammation Research Center, a VIB-UGent Department UGent Department of Internal Medicine, Respiratory Medicine (GE01) Technologiepark 927 , B-9052 Zwijnaarde , Belgium Tel : +32(0)9 331 37 40 Fax : +32(0)9 221 76 73 Mailto: yvan.saeys@ugent.be http://www.dambi.ugent.be ======================================================================