PUB - Publikationen an der Universität Bielefeld

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• [18]
  

  2021 | Bielefelder E-Dissertation | PUB-ID: 2956362

  B. Hosseini, Interpretable analysis of motion data, Bielefeld: Universität Bielefeld, 2021.

  PUB | PDF | DOI
   
• [17]
  

  2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982082

  B. Hosseini and B. Hammer, “Large-Margin Multiple Kernel Learning for Discriminative Features Selection and Representation Learning”, 2019 International Joint Conference on Neural Networks (IJCNN), IEEE, 2019, pp.1-8.

  PUB | DOI
   
• [16]
  

  2019 | Konferenzbeitrag | Angenommen | PUB-ID: 2937842

  B. Hosseini and B. Hammer, “Deep-Aligned Convolutional Neural Network for Skeleton-based Action Recognition and Segmentation”, Presented at the 2019 IEEE International Conference on Data Mining (ICDM), Beijing, Accepted.

  PUB | Datei | arXiv
   
• [15]
  

  2019 | Konferenzbeitrag | Angenommen | PUB-ID: 2937841

  B. Hosseini and B. Hammer, “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, Accepted.

  PUB | Datei | arXiv
   
• [14]
  

  2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2937839

  B. Hosseini and B. Hammer, “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, 2019.

  PUB | Datei | arXiv
   
• [13]
  

  2019 | Konferenzbeitrag | PUB-ID: 2930303

  B. Hosseini and B. Hammer, “Multiple-Kernel Dictionary Learning for Reconstruction and Clustering of Unseen Multivariate Time-series”, Proceedings of the 27th European Symposium on Artificial Neural Networks (ESANN 2019), M. Verleysen, ed., 2019.

  PUB | arXiv
   
• [12]
  

  2019 | Konferenzbeitrag | PUB-ID: 2934192

  B. Hosseini and B. Hammer, “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, 2019.

  PUB | arXiv
   
• [11]
  

  2018 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2982090

  B. Hosseini and B. Hammer, “Non-negative Local Sparse Coding for Subspace Clustering”, Advances in Intelligent Data Analysis XVII. 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24–26, 2018, Proceedings, W. Duivesteijn, A. Siebes, and A. Ukkonen, eds., Lecture Notes in Computer Science, Cham: Springer International Publishing, 2018, pp.137-150.

  PUB | DOI
   
• [10]
  

  2018 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982087

  B. Hosseini and B. Hammer, “Confident Kernel Sparse Coding and Dictionary Learning”, 2018 IEEE International Conference on Data Mining (ICDM), IEEE, 2018, pp.1031-1036.

  PUB | DOI
   
• [9]
  

  2018 | Preprint | Veröffentlicht | PUB-ID: 2921209

  B. Hosseini and B. Hammer, “Non-Negative Local Sparse Coding for Subspace Clustering”, Advances in Intelligent Data Analysis XVII. IDA 2018, 2018.

  PUB | Datei | Download (ext.) | arXiv
   
• [8]
  

  2018 | Konferenzbeitrag | Im Druck | PUB-ID: 2932116

  B. Hosseini and B. Hammer, “Confident Kernel Sparse Coding and Dictionary Learning”, 2018 IEEE International Conference on Data Mining (ICDM), In Press.

  PUB | Datei | arXiv
   
• [7]
  

  2018 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2919598

  B. Hosseini and B. Hammer, “Feasibility Based Large Margin Nearest Neighbor Metric Learning”, ESANN 2018. Proceedings of 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, 2018, pp.219-224.

  PUB | arXiv
   
• [6]
  

  2017 | Kurzbeitrag Konferenz / Poster | PUB-ID: 2919987

  B. Hosseini and B. Hammer, “Non-negative Kernel Sparse Coding Frameworks for Efficient Analysis of Motion Data”, Presented at the BMVA Symposium on Human Activity Recognition and Monitoring, London, 2017.

  PUB | PDF
   
• [5]
  

  2017 | Kurzbeitrag Konferenz / Poster | PUB-ID: 2919990

  B. Hosseini and B. Hammer, “Task-Driven Sparse Coding for Classification of Motion Data”, Presented at the Ninth Mittweida Workshop on Computational Intelligence (MiWoCI 2017), Mittweida, 2017.

  PUB | PDF
   
• [4]
  

  2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2904469

  B. Hosseini, et al., “Non-Negative Kernel Sparse Coding for the Analysis of Motion Data”, Artificial Neural Networks and Machine Learning – ICANN 2016, A. E.P. Villa, P. Masulli, and A. Javier Pons Rivero, eds., Lecture Notes in Computer Science, vol. 9887, Cham: Springer, 2016, pp.506-514.

  PUB | PDF | DOI | Download (ext.) | arXiv
   
• [3]
  

  2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2783165

  B. Hosseini and B. Hammer, “Efficient Metric Learning for the Analysis of Motion Data”, 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA), Piscataway, NJ: IEEE, 2015.

  PUB | DOI | Download (ext.) | arXiv
   
• [2]
  

  2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2914986

  B. Hosseini, M.N. Ahmadabadi, and B.N. Araabi, “Abstract Concept Learning Approach Based on Behavioural Feature Extraction”, 2009 Second International Conference on Computer and Electrical Engineering, J. Kamaruzaman, ed., vol. 2, Piscataway, NJ: IEEE, 2010.

  PUB | PDF | DOI
   
• [1]
  

  2008 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2914988

  M.R. Jamali, et al., “Real Time Emotional Control for Anti-Swing and Positioning Control of SIMO Overhead Traveling Crane”, International Journal of Innovative Computing, Information, and Control, vol. 4, 2008, pp. 2333-2344.

  PUB | PDF