18 Publikationen
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2019 | Konferenzbeitrag | Angenommen | PUB-ID: 2937841Hosseini, B., and Hammer, B. (Accepted).“Interpretable Multiple-Kernel Prototype Learning for Discriminative Representation and Feature Selection”. Presented at the The 28th ACM International Conference on Information and Knowledge Management (CIKM) , Beijing.PUB | Datei | arXiv
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2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2937839Hosseini, B., and Hammer, B. (2019).“Interpretable Discriminative Dimensionality Reduction and Feature Selection on the Manifold”. Presented at the 2019 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML), Würzburg.PUB | Datei | arXiv
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2019 | Konferenzbeitrag | PUB-ID: 2930303Hosseini, B., and Hammer, B. (2019). “Multiple-Kernel Dictionary Learning for Reconstruction and Clustering of Unseen Multivariate Time-series” in Proceedings of the 27th European Symposium on Artificial Neural Networks (ESANN 2019), Verleysen, M. ed.PUB | arXiv
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2018 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2982090Hosseini, B., and Hammer, B. (2018). “Non-negative Local Sparse Coding for Subspace Clustering” in Advances in Intelligent Data Analysis XVII. 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24–26, 2018, Proceedings, Duivesteijn, W., Siebes, A., and Ukkonen, A. eds. Lecture Notes in Computer Science (Cham: Springer International Publishing), 137-150.PUB | DOI
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2018 | Preprint | Veröffentlicht | PUB-ID: 2921209Hosseini, B., and Hammer, B. (2018). Non-Negative Local Sparse Coding for Subspace Clustering. Advances in Intelligent Data Analysis XVII. IDA 2018.PUB | Datei | Download (ext.) | arXiv
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2018 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2919598Hosseini, B., and Hammer, B. (2018). “Feasibility Based Large Margin Nearest Neighbor Metric Learning” in ESANN 2018. Proceedings of 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning 219-224.PUB | arXiv
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2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2904469Hosseini, B., Hülsmann, F., Botsch, M., and Hammer, B. (2016). “Non-Negative Kernel Sparse Coding for the Analysis of Motion Data” in Artificial Neural Networks and Machine Learning – ICANN 2016, E.P. Villa, A., Masulli, P., and Javier Pons Rivero, A. eds. Lecture Notes in Computer Science, vol. 9887, (Cham: Springer), 506-514.PUB | PDF | DOI | Download (ext.) | arXiv
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2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2783165Hosseini, B., and Hammer, B. (2015). “Efficient Metric Learning for the Analysis of Motion Data” in 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA) (Piscataway, NJ: IEEE).PUB | DOI | Download (ext.) | arXiv
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2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2914986Hosseini, B., Ahmadabadi, M. N., and Araabi, B. N. (2010). “Abstract Concept Learning Approach Based on Behavioural Feature Extraction” in 2009 Second International Conference on Computer and Electrical Engineering, Kamaruzaman, J. ed., vol. 2, (Piscataway, NJ: IEEE).PUB | PDF | DOI
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2008 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2914988Jamali, M. R., Arami, A., Hosseini, B., Moshiri, B., and Lukas, C. (2008). Real Time Emotional Control for Anti-Swing and Positioning Control of SIMO Overhead Traveling Crane. International Journal of Innovative Computing, Information, and Control 4, 2333-2344.PUB | PDF