Accepted Papers

Proceedings available as a single PDF file.

Accepted for oral presentation

• Be In The Know: Connecting News Articles to Relevant Twitter Conversations (Bichen Shi, Georgiana Ifrim and Neil Hurley)
• Recommender-based Multiple Classifier System (Yury Kashnitsky, Dmitry Ignatov and Sergei Kuznetsov)
• Inference of Switched Biochemical Reaction Networks Using Sparse Bayesian Learning (Wei Pan, Ye Yuan, Aivar Sootla and Guy-Bart Stan)
• Clustering Boolean Tensors (Saskia Metzler and Pauli Miettinen)
• Search for User-related Features in Matrix Factorization-based Recommender Systems (Marharyta Aleksandrova, Armelle Brun, Anne Boyer and Oleg Chertov)
• Heterogeneous Bayes Filters with Sparse Bayesian Models: Application to state estimation in robotics (Alexandre Ravet and Simon Lacroix)
• Optimistic Active Learning for Classification (Timothé Collet and Olivier Pietquin)
• On Improving Operational Planning and Control in Public Transportation Networks using Streaming Data: A Machine Learning Approach (Luis Moreira-Matias, Joao Moreira, Joao Gama and Michel Ferreira)

Accepted as poster

• Generalizing, Optimizing, and Decoding Support Vector Machine Classification (Mario Michael Krell, Sirko Straube, Hendrik Wöhrle and Frank Kirchner)
• Heterogeneous Dataflow Hardware Accelerators for Machine Learning on Reconfigurable Hardware (Hendrik Wöhrle, Johannes Teiwes, Mario Michael Krell, Anett Seeland, Elsa Kirchner and Frank Kirchner)
• Evaluating Collaborative Filtering: Methods within a Binary Purchase Setting (Stijn Geuens, Kristof Coussement and Koen De Bock)
• An opinion mining Partial Least Square Path Modeling for football betting (Mohamed El Hamdaoui and Jean-Valère Cossu)
• Multivariate Normal Distribution Based Multi-Armed Bandits Pareto Algorithm (Saba Yahyaa, Madalina Drugan and Bernard Manderick)
• Managing Ventilation Systems for Improving User Comfort in Smart Buildings using Reinforcement Learning Agents (Jiawei Zhu, Fabrice Lauri, Abderrafiaa Koukam and Vincent Hilaire)
• Robust Optimization using Machine Learning for Uncertainty Sets (Theja Tulabandhula)
• Parallel Learning Algorithm for Large-Scale Regression with Additive Models (Valeriy Khakhutskyy and Markus Hegland)
• A Framework for Pattern Classifier Selection and Fusion (Fabio Faria, Anderson Rocha and Ricardo Torres)
• Affinity Analysis between Researchers using Text Mining and Differential Analysis of Graphs (Luis Trigo and  Pavel Brazdil)
• NASSAU: Description Length Minimization for Boolean Matrix Factorization (Sanjar Karaev)