intelligent machines
17 november 2010
"de vereeniging", nijmegen, the netherlands


1 Bahramisharif, A., Gerven, van M., Heskes, T., Jensen, O.Covert attention allows for continuous control of brain-computer interfacesRadboud University, ICISNijmegen
2 Birlutiu, A., Groot, P., Dijkstra, T., Heskes, T.Personalization of hearing aids through bayesian preference elicitationRadboud University, ICISNijmegen
3 Bodegraven, K., Logtmeijer, R., Janssen, J.Intelligent control systems for navy shipsDefence Materiel OrganisationDen Haag
4 Bosch, van den, A.Implicit linguistics: machine learning of text-to-text processingTilburg center for Communication and CognitionTilburg
5 Broek, van den, B., Wiegerinck, W., Kappen, B.,Risk sensitive path integral controlRadboud University, SNNNijmegen
6 Burgers, W., Wiegerinck, W.Bonaparte: disaster victim identification systemSMART Research B.V., SNNNijmegen
7 Burgers, W., Wiegerinck, W., Kappen, B., Spalburg, M.A bayesian petrophysical decision support system for estimation of reservoir compositionsSMART Research B.V., SNNNijmegen
8 Busoniu, L., Zhang, F., Babuška, R.Online policy iteration for real-time control: A learning system demonstratorTU Delft, Center for Systems and ControlDelft
9 Claassen, T., Heskes, T.Causal discovery from multiple modelsRadboud University, ICISNijmegen
10Gerven, M., Lange, de, F., Heskes, T.A hierarchical generative model for percept reconstructionRadboud University, ICISNijmegen
11Gheshlaghi Azar, M., Kappen, B.Dynamic policy programming by KL-divergence minimizationRadboud University, SNNNijmegen
12Gómez, V., Kappen, B., Kaltenbrunner, A.Modeling the structure and evolution of discussion cascadesRadboud University, SNNNijmegen
13Graus, M.Understanding the latent features in recommender systemsTUE, Industrial Engineering and Innovation SciencesEindhoven
14Eiben, A.E., Haasdijk, E.On-the-Fly evolution for robotsVU University, Faculty of SciencesAmsterdam
15Hogeweg, L., Mol, C., Jong, de, P., Ginneken, B.Fusion of local and global detection systems to detect tuberculosis in chest radiographsUMCU, Image Science InstituteUtrecht
16Ibba, A., Duin, R., Wan-Jui, L.Merging multiple sources of information using dissimilarity based approachesTU Delft, Pattern Recognition LaboratoryDelft
17Jansen, B., Sahli, H., Lemeire, J.Learning dynamic data modelsVUB Department Electronics and InformaticsBrussel
18Janssens, J., Postma, E.Unsupervised outlier selection with pairwise affinitiesTilburg center for Cognition and CommunicationTilburg
19Tuyls, K., Weiss, G., Bloembergen, D., Hennes, D., Jong, de, Steven, Lemmens, N., Kaisers, M.SwarmLab stigmergic landmark foraging on real robotsMaastricht University, Knowledge EngineeringMaastricht
20Kappen., B., Akay, E., Neijt, J. Promedas: a medical diagnostic expert systemRadboud University/ SNN, UMCUNijmegen/Utrecht
21Snoeren, P., Litjens, G., Grinneken, van, B., Karssemeijer, N.Training a computer aided detection system with simulated lung nodules in chest radiographsRadboud UMCNijmegen
22Li, Y., Tax, D., Duin, R., Loog, M.Maximum membership scale selectionTU Delft, Pattern Recognition LaboratoryDelft
23Loog, M.Constrained parameter estimation for semi-supervised learningTU Delft, Pattern Recognition LaboratoryDelft
24Lue, T.K., Rijken, R.J., Merk, R.J., Roessingh J.J.Smart Bandits: A machine learning approach to air to air combatNLRAmsterdam
25Marck, J.W.Hostile intent – an intelligent camera recognizes abnormal behavior of peopleTNO Defence, Security and SafetyDen Haag
26Meij, van der, R.A genetic algorithm for solving slope stability problems: from Bishop to an unconstrained slip planeDeltares & Delft University of TechnologyDelft
27Mens, A.Using bayesian belief nets to predict failures within foundation engineeringDeltares & TU DelftDelft
28Mesman, B., Mouton, L., Wijnings, P.Neural Pong: a study of human-machine interaction in a restricted worldTUE, Electrical EngineeringEindhoven
29Asch, van, V., Morante, R., Daelemans, W.BIOGRAPHTA Large scale biomedical relation extraction from unstructured dataCLiPS - University of AntwerpAntwerpen
30Neumann, M., Herik, van der, J., Postma, E., Grant, T.Enabling sensemaking using machine learning techniquesUniversity of Tilburg, TiCCTilburg
31Oude, P., Pavlin, G.A distributed approach to bayesian modeling and inference.Thales Research & Technology NetherlandsDelft
32Peemen, M., Mesman, B.Convolutional neural networks applied to visual object recognitionTUE, Electrical EngineeringEindhoven
33Pontier, M.An affective virtual agent for natural human-agent interactionVU CAMeRAAmsterdam
34Postma, E., Janssens, J.Ranking images on semantic attributes using human computationTilburg center for Cognition and CommunicationTilburg
35Rooij, S., Koolen, W.Switching investmentsCWIAmsterdam
36Rudinac, M., Jonker, P.How to focus robot′s attention?TU Delft, Biorobotics labDelft
37Sánchez, C., Ginneken, B.Active learning for an efficient training strategy of computer-aided diagnosis systems: application to diabetic retinopathy screeningRadboud UMCNijmegen
38Seijen, van, H., Whiteson, S.Efficient reinforcement learning by approximating the best-match valuesUvA, Informatics InstituteAmsterdam
39Janssen, A., Tsivtsivadze, E., Boberg, J., Dijkstra, T., Heskes, H.Efficient remote homology detectionRadboud University, ICISNijmegen
40Vromen, T., Steur E., Nijmeijer, H.Training in neuronal clustersTUE, Mechanical EngineeringEindhoven
41Wiegerinck, W.Statistical modeling artificial reasoning technologySMART Research B.V., SNNNijmegen
42Zant, van der, T.RoboCup@Home: a test-bed for intelligent machinesUniversity of Groningen, Artificial IntelligenceGroningen
43Duin, R.P.W., Orozco-Alzate, M., Makario Londoño-Bonilla, J.Classification of volcano events observed by multiple seismic stationsDelft University of TechnologyDelft