SNN Symposium 2010: Intelligent Machines

abstracts

1	Bahramisharif, A., Gerven, van M., Heskes, T., Jensen, O.	Covert attention allows for continuous control of brain-computer interfaces	Radboud University, ICIS	Nijmegen
2	Birlutiu, A., Groot, P., Dijkstra, T., Heskes, T.	Personalization of hearing aids through bayesian preference elicitation	Radboud University, ICIS	Nijmegen
3	Bodegraven, K., Logtmeijer, R., Janssen, J.	Intelligent control systems for navy ships	Defence Materiel Organisation	Den Haag
4	Bosch, van den, A.	Implicit linguistics: machine learning of text-to-text processing	Tilburg center for Communication and Cognition	Tilburg
5	Broek, van den, B., Wiegerinck, W., Kappen, B.,	Risk sensitive path integral control	Radboud University, SNN	Nijmegen
6	Burgers, W., Wiegerinck, W.	Bonaparte: disaster victim identification system	SMART Research B.V., SNN	Nijmegen
7	Burgers, W., Wiegerinck, W., Kappen, B., Spalburg, M.	A bayesian petrophysical decision support system for estimation of reservoir compositions	SMART Research B.V., SNN	Nijmegen
8	Busoniu, L., Zhang, F., Babuška, R.	Online policy iteration for real-time control: A learning system demonstrator	TU Delft, Center for Systems and Control	Delft
9	Claassen, T., Heskes, T.	Causal discovery from multiple models	Radboud University, ICIS	Nijmegen
10	Gerven, M., Lange, de, F., Heskes, T.	A hierarchical generative model for percept reconstruction	Radboud University, ICIS	Nijmegen
11	Gheshlaghi Azar, M., Kappen, B.	Dynamic policy programming by KL-divergence minimization	Radboud University, SNN	Nijmegen
12	Gómez, V., Kappen, B., Kaltenbrunner, A.	Modeling the structure and evolution of discussion cascades	Radboud University, SNN	Nijmegen
13	Graus, M.	Understanding the latent features in recommender systems	TUE, Industrial Engineering and Innovation Sciences	Eindhoven
14	Eiben, A.E., Haasdijk, E.	On-the-Fly evolution for robots	VU University, Faculty of Sciences	Amsterdam
15	Hogeweg, L., Mol, C., Jong, de, P., Ginneken, B.	Fusion of local and global detection systems to detect tuberculosis in chest radiographs	UMCU, Image Science Institute	Utrecht
16	Ibba, A., Duin, R., Wan-Jui, L.	Merging multiple sources of information using dissimilarity based approaches	TU Delft, Pattern Recognition Laboratory	Delft
17	Jansen, B., Sahli, H., Lemeire, J.	Learning dynamic data models	VUB Department Electronics and Informatics	Brussel
18	Janssens, J., Postma, E.	Unsupervised outlier selection with pairwise affinities	Tilburg center for Cognition and Communication	Tilburg
19	Tuyls, K., Weiss, G., Bloembergen, D., Hennes, D., Jong, de, Steven, Lemmens, N., Kaisers, M.	SwarmLab stigmergic landmark foraging on real robots	Maastricht University, Knowledge Engineering	Maastricht
20	Kappen., B., Akay, E., Neijt, J.	Promedas: a medical diagnostic expert system	Radboud University/ SNN, UMCU	Nijmegen/Utrecht
21	Snoeren, P., Litjens, G., Grinneken, van, B., Karssemeijer, N.	Training a computer aided detection system with simulated lung nodules in chest radiographs	Radboud UMC	Nijmegen
22	Li, Y., Tax, D., Duin, R., Loog, M.	Maximum membership scale selection	TU Delft, Pattern Recognition Laboratory	Delft
23	Loog, M.	Constrained parameter estimation for semi-supervised learning	TU Delft, Pattern Recognition Laboratory	Delft
24	Lue, T.K., Rijken, R.J., Merk, R.J., Roessingh J.J.	Smart Bandits: A machine learning approach to air to air combat	NLR	Amsterdam
25	Marck, J.W.	Hostile intent – an intelligent camera recognizes abnormal behavior of people	TNO Defence, Security and Safety	Den Haag
26	Meij, van der, R.	A genetic algorithm for solving slope stability problems: from Bishop to an unconstrained slip plane	Deltares & Delft University of Technology	Delft
27	Mens, A.	Using bayesian belief nets to predict failures within foundation engineering	Deltares & TU Delft	Delft
28	Mesman, B., Mouton, L., Wijnings, P.	Neural Pong: a study of human-machine interaction in a restricted world	TUE, Electrical Engineering	Eindhoven
29	Asch, van, V., Morante, R., Daelemans, W.	BIOGRAPHTA Large scale biomedical relation extraction from unstructured data	CLiPS - University of Antwerp	Antwerpen
30	Neumann, M., Herik, van der, J., Postma, E., Grant, T.	Enabling sensemaking using machine learning techniques	University of Tilburg, TiCC	Tilburg
31	Oude, P., Pavlin, G.	A distributed approach to bayesian modeling and inference.	Thales Research & Technology Netherlands	Delft
32	Peemen, M., Mesman, B.	Convolutional neural networks applied to visual object recognition	TUE, Electrical Engineering	Eindhoven
33	Pontier, M.	An affective virtual agent for natural human-agent interaction	VU CAMeRA	Amsterdam
34	Postma, E., Janssens, J.	Ranking images on semantic attributes using human computation	Tilburg center for Cognition and Communication	Tilburg
35	Rooij, S., Koolen, W.	Switching investments	CWI	Amsterdam
36	Rudinac, M., Jonker, P.	How to focus robot′s attention?	TU Delft, Biorobotics lab	Delft
37	Sánchez, C., Ginneken, B.	Active learning for an efficient training strategy of computer-aided diagnosis systems: application to diabetic retinopathy screening	Radboud UMC	Nijmegen
38	Seijen, van, H., Whiteson, S.	Efficient reinforcement learning by approximating the best-match values	UvA, Informatics Institute	Amsterdam
39	Janssen, A., Tsivtsivadze, E., Boberg, J., Dijkstra, T., Heskes, H.	Efficient remote homology detection	Radboud University, ICIS	Nijmegen
40	Vromen, T., Steur E., Nijmeijer, H.	Training in neuronal clusters	TUE, Mechanical Engineering	Eindhoven
41	Wiegerinck, W.	Statistical modeling artificial reasoning technology	SMART Research B.V., SNN	Nijmegen
42	Zant, van der, T.	RoboCup@Home: a test-bed for intelligent machines	University of Groningen, Artificial Intelligence	Groningen
43	Duin, R.P.W., Orozco-Alzate, M., Makario Londoño-Bonilla, J.	Classification of volcano events observed by multiple seismic stations	Delft University of Technology	Delft