18 Publikationen

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  • [18]
    2021 | Bielefelder E-Dissertation | PUB-ID: 2956362 OA
    Hosseini, B., 2021. Interpretable analysis of motion data, Bielefeld: Universität Bielefeld.
    PUB | PDF | DOI
     
  • [17]
    2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982082
    Hosseini, B., & Hammer, B., 2019. Large-Margin Multiple Kernel Learning for Discriminative Features Selection and Representation Learning. In 2019 International Joint Conference on Neural Networks (IJCNN). IEEE, pp. 1-8.
    PUB | DOI
     
  • [16]
    2019 | Konferenzbeitrag | Angenommen | PUB-ID: 2937842 OA
    Hosseini, B., & Hammer, B., Accepted. Deep-Aligned Convolutional Neural Network for Skeleton-based Action Recognition and Segmentation. Presented at the 2019 IEEE International Conference on Data Mining (ICDM), Beijing.
    PUB | Datei | arXiv
     
  • [15]
    2019 | Konferenzbeitrag | Angenommen | PUB-ID: 2937841 OA
    Hosseini, B., & 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
     
  • [14]
    2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2937839 OA
    Hosseini, B., & 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
     
  • [13]
    2019 | Konferenzbeitrag | PUB-ID: 2930303
    Hosseini, B., & Hammer, B., 2019. Multiple-Kernel Dictionary Learning for Reconstruction and Clustering of Unseen Multivariate Time-series. In M. Verleysen, ed. Proceedings of the 27th European Symposium on Artificial Neural Networks (ESANN 2019).
    PUB | arXiv
     
  • [12]
    2019 | Konferenzbeitrag | PUB-ID: 2934192
    Hosseini, B., & Hammer, B., 2019. Large-Margin Multiple Kernel Learning for Discriminative Features Selection and Representation Learning. Presented at the The 2019 International Joint Conference on Neural Networks (IJCNN), Budapest.
    PUB | arXiv
     
  • [11]
    2018 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2982090
    Hosseini, B., & Hammer, B., 2018. Non-negative Local Sparse Coding for Subspace Clustering. In W. Duivesteijn, A. Siebes, & A. Ukkonen, eds. Advances in Intelligent Data Analysis XVII. 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24–26, 2018, Proceedings. Lecture Notes in Computer Science. Cham: Springer International Publishing, pp. 137-150.
    PUB | DOI
     
  • [10]
    2018 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982087
    Hosseini, B., & Hammer, B., 2018. Confident Kernel Sparse Coding and Dictionary Learning. In 2018 IEEE International Conference on Data Mining (ICDM). IEEE, pp. 1031-1036.
    PUB | DOI
     
  • [9]
    2018 | Preprint | Veröffentlicht | PUB-ID: 2921209 OA
    Hosseini, B., & Hammer, B., 2018. Non-Negative Local Sparse Coding for Subspace Clustering. Advances in Intelligent Data Analysis XVII. IDA 2018.
    PUB | Datei | Download (ext.) | arXiv
     
  • [8]
    2018 | Konferenzbeitrag | Im Druck | PUB-ID: 2932116 OA
    Hosseini, B., & Hammer, B., In Press. Confident Kernel Sparse Coding and Dictionary Learning. In 2018 IEEE International Conference on Data Mining (ICDM).
    PUB | Datei | arXiv
     
  • [7]
    2018 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2919598
    Hosseini, B., & 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. pp. 219-224.
    PUB | arXiv
     
  • [6]
    2017 | Kurzbeitrag Konferenz / Poster | PUB-ID: 2919987 OA
    Hosseini, B., & Hammer, B., 2017. Non-negative Kernel Sparse Coding Frameworks for Efficient Analysis of Motion Data. Presented at the BMVA Symposium on Human Activity Recognition and Monitoring, London.
    PUB | PDF
     
  • [5]
    2017 | Kurzbeitrag Konferenz / Poster | PUB-ID: 2919990 OA
    Hosseini, B., & Hammer, B., 2017. Task-Driven Sparse Coding for Classification of Motion Data. Presented at the Ninth Mittweida Workshop on Computational Intelligence (MiWoCI 2017), Mittweida.
    PUB | PDF
     
  • [4]
    2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2904469 OA
    Hosseini, B., et al., 2016. Non-Negative Kernel Sparse Coding for the Analysis of Motion Data. In A. E.P. Villa, P. Masulli, & A. Javier Pons Rivero, eds. Artificial Neural Networks and Machine Learning – ICANN 2016. Lecture Notes in Computer Science. no.9887 Cham: Springer, pp. 506-514.
    PUB | PDF | DOI | Download (ext.) | arXiv
     
  • [3]
    2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2783165
    Hosseini, B., & 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
     
  • [2]
    2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2914986 OA
    Hosseini, B., Ahmadabadi, M.N., & Araabi, B.N., 2010. Abstract Concept Learning Approach Based on Behavioural Feature Extraction. In J. Kamaruzaman, ed. 2009 Second International Conference on Computer and Electrical Engineering. no.2 Piscataway, NJ: IEEE.
    PUB | PDF | DOI
     
  • [1]
    2008 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2914988 OA
    Jamali, M.R., et al., 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(9), p 2333-2344.
    PUB | PDF
     

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