[Home][Call for Papers][Program]
9:00-10:30 | Challenges in Robotics Matthias Rolf, Jochen Steil (Bielefeld University): Explorative learning of right inverse functions: theoretical implications of redundancy Mathias Klingner1, Sven Hellbach1, Marika Kästner2, Thomas Villmann2, Hans-Joachim Böhme1 (1-University of Applied Sciences Dresden, 2-University of Applied Sciences Mittweida): Modeling Human Movements by Self-Organizing Maps using Adaptive Metrics Jakob Gütschow, Johannes Lohmann, Danil Koryakin, and Martin V. Butz (University of Tübingen): Learning Motor Primitives with Echo State Networks Sven Hellbach, Hans-Joachim Böhme (University of Applied Sciences Dresden): Robotics with the head in the clouds |
10:30-11:00 | Coffee break |
11:00-12:00 |
Learning non-Euclidean data Emil Eirola1, Amaury Lendasse1, Vincent Vandewalle2, Christophe Biernacki2 (1-Aalto University, 2-University of Lille): Mixture of Gaussians for distance estimation with missing data Thomas Villmann, Marika Kaestner, David Nebel, Martin Riedel (University of Applied Sciences Mittweida): Enhancement Learning in Functional Relevance Learning Vector Quantization Daniela Hofmann, Andrej Gisbrecht, Barbara Hammer (Bielefeld University): Discriminative probabilistic prototype based models in kernel space |
12:00-13:00 | Keynote talk Prof. Dr. Michel Verleysen (Université catholique de Louvain, Engineering Faculty - Electricity Department): Information theoretic feature selection for high-dimensional data analysis |
13:00-14:00 | Lunch break |
14:00-15:30 |
Visualization, Interpretation, and Sparsity Marc Strickert (Philipps University Marburg): No Perplexity in Stochastic Neighbor Embedding Alexander Schulz, Andrej Gisbrecht, Kerstin Bunte, and Barbara Hammer (Bielefeld University): How to visualize a classifier? Slobodan Vukanovic, Nicole Carey, Robert Haschke, Helge Ritter (Bielefeld University): Locally Weighted Regression using an Error-based Allocation Strategy Andreas Backhaus, Udo Seiffert (Fraunhofer IFF): Classification in High-dimensional Spectral Data - Precision vs. Interpretability vs. Model Size |
15:30-16:00 | Coffee break |
16:00-17:00 |
Invariances and Feature Learning Marian Himstedt, Sven Hellbach, Hans-Joachim Böhme (University of Applied Sciences Dresden): Feature extraction from Occupancy Grid Maps using Non-negative Matrix Factorization Markus Lessmann, Rolf Würtz (Ruhr-University Bochum): Learning of Invariant Object Recognition in a Hierarchical Network Jens Hocke, Thomas Martinetz (University of Lübeck): Experience in Training (Deep) Multi-Layer Perceptrons to Classify Digits |
17:00-17:20 | Discussion: Hot challenges in Neural Computation |
17:20-17:30 | Nomination of the best presentation award and closing |
starting from 17:30 | Meeting of the German Neural Network Society and the GI Arbeitskreis Neuronale Netze |
19:30-21:30 | Welcome reception of DAGM at the old University (venue) |
The workshop proceedings will be available online in the series Machine Learning Reports.
Barbara Hammer |