1. MichałAntkiewicz, Kacper Bąk, Alexandr Murashkin, Rafael Olaechea, Jia Hui (Jimmy) Liang & Krzysztof Czarnecki (2013): Clafer Tools for Product Line Engineering. In: Proceedings of the 17th International Software Product Line Conference Co-located Workshops, SPLC '13 Workshops. ACM, pp. 130–135, doi:10.1145/2499777.2499779.
  2. Davide Bacciu, Paolo Barsocchi, Stefano Chessa, Claudio Gallicchio & Alessio Micheli (2014): An experimental characterization of reservoir computing in ambient assisted living applications. Neural Computing and Applications 24(6), pp. 1451–1464, doi:10.1007/s00521-013-1364-4.
  3. M. H. ter Beek, A. Fantechi & S. Gnesi (2014): Challenges in Modelling and Analyzing Quantitative Aspects of Bike-Sharing Systems. In: T. Margaria & B. Steffen: Proceedings of the 6th International Symposium on Leveraging Applications of Formal Methods, Verification and Validation (ISoLA'14), LNCS 8802. Springer, pp. 351–367, doi:10.1007/978-3-662-45234-9_25.
  4. M. H. ter Beek, A. Fantechi, S. Gnesi & F. Mazzanti (2014): A collection of models of a bike-sharing case study. Technical Report TR-QC-07-2014.
  5. M. H. ter Beek, S. Gnesi & A. Fantechi (2013): Chaining available tools to support the modelling and analysis of a bike-sharing product line: An experience report. Technical Report TR-QC-02-2013.
  6. David Benavides, Pablo Trinidad & Antonio Ruiz-Cortés (2013): Automated Reasoning on Feature Models. In: Seminal Contributions to Information Systems Engineering. Springer, pp. 361–373, doi:10.1007/11431855_34.
  7. Kacper Bąk (2013): Modeling and Analysis of Software Product Line Variability in Clafer. University of Waterloo.
  8. Chih-Chung Chang & Chih-Jen Lin (2011): LIBSVM: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology 2, pp. 27:1–27:27, doi:10.1145/1961189.1961199. Software available at
  9. R. Collobert & S. Bengio (2001): SVMTorch: Support Vector Machines for Large-Scale Regression Problems. Journal of Machine Learning Research 1, pp. 143–160, doi:10.1162/15324430152733142.
  10. Etienne Come, Njato Andry Randriamanamihaga, Latifa Oukhellou & Patrice Aknin (2014): Spatio-temporal Analysis of Dynamic Origin-Destination Data Using Latent Dirichlet Allocation: Application to Vélib' Bike Sharing System of Paris. In: TRB 93rd Annual meeting, France. Available at
  11. Lise Getoor & Ben Taskar (2007): Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning). The MIT Press.
  12. Romain Giot & Raphaël Cherrier (2014): Predicting bikeshare system usage up to one day ahead. In: Computational Intelligence in Vehicles and Transportation Systems (CIVTS), 2014 IEEE Symposium on. IEEE, pp. 22–29, doi:10.1109/CIVTS.2014.7009473.
  13. T. Joachims (1999): Making large-Scale SVM Learning Practical. In: B. Schölkopf, C. Burges & A. Smola: Advances in Kernel Methods - Support Vector Learning, chapter 11. MIT Press, Cambridge, MA, pp. 169–184.
  14. Stefan C. Kremer (2001): Field Guide to Dynamical Recurrent Networks. Wiley-IEEE Press, doi:10.1109/9780470544037.fmatter.
  15. Mantas Lukoševičius & Herbert Jaeger (2009): Reservoir Computing Approaches to Recurrent Neural Network Training. Comput. Sci. Rev. 3(3), pp. 127–149, doi:10.1016/j.cosrev.2009.03.005.
  16. Alexandr Murashkin, MichałAntkiewicz, Derek Rayside & Krzysztof Czarnecki (2013): Visualization and Exploration of Optimal Variants in Product Line Engineering. In: Software Product Line Conference, Tokyo, Japan, doi:10.1145/2491627.2491647.
  17. Andrew Y. Ng & Michael I. Jordan (2002): On Discriminative vs. Generative Classifiers: A comparison of logistic regression and naive Bayes. In: T.G. Dietterich, S. Becker & Z. Ghahramani: Advances in Neural Information Processing Systems 14. MIT Press, pp. 841–848.
  18. Judea Pearl (2000): Causality: Models, Reasoning, and Inference. Cambridge University Press, New York, NY, USA.
  19. John Shawe-Taylor & Nello Cristianini (2004): Kernel Methods for Pattern Analysis. Cambridge University Press, New York, NY, USA, doi:10.1017/CBO9780511809682.
  20. Samaneh Soltani, Mohsen Asadi, Dragan Gaševi\'c, Marek Hatala & Ebrahim Bagheri (2012): Automated Planning for Feature Model Configuration Based on Functional and Non-functional Requirements. In: Proceedings of the 16th International Software Product Line Conference - Volume 1, SPLC '12. ACM, New York, NY, USA, pp. 56–65, doi:10.1145/2362536.2362548.
  21. Jilles Van Gurp, Jan Bosch & Mikael Svahnberg (2001): On the notion of variability in software product lines. In: Software Architecture, 2001. Proceedings. Working IEEE/IFIP Conference on. IEEE, pp. 45–54, doi:10.1109/WICSA.2001.948406.

Comments and questions to:
For website issues: