Bassam Mokbel

bmokbel@techfak.uni-bielefeld.de
PEVZ-ID
18880650

41 Publikationen

Alle markieren

  • [41]
    2016 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2783224 OA
    B. Paaßen, B. Mokbel, and B. Hammer, “Adaptive structure metrics for automated feedback provision in intelligent tutoring systems”, Neurocomputing, vol. 192, 2016, pp. 3-13.
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  • [40]
    2016 | Bielefelder E-Dissertation | PUB-ID: 2900425 OA
    B. Mokbel, Dissimilarity-based learning for complex data, Bielefeld: Universität Bielefeld, 2016.
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  • [39]
    2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2752948 OA
    S. Gross, et al., “Learning Feedback in Intelligent Tutoring Systems. Report of the FIT Project, Conducted from December 2011 to March 2015”, KI - Künstliche Intelligenz, vol. 29, 2015, pp. 413-418.
    PUB | PDF | DOI | Download (ext.) | WoS
     
  • [38]
    2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2903777 OA
    A. Schulz, et al., “Inferring Feature Relevances From Metric Learning”, 2015 IEEE Symposium Series on Computational Intelligence, Piscataway, NJ: IEEE, 2015.
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  • [37]
    2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2710031 OA
    B. Mokbel, et al., “Metric learning for sequences in relational LVQ”, Neurocomputing, vol. 169, 2015, pp. 306-322.
    PUB | PDF | DOI | Download (ext.) | WoS
     
  • [36]
    2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2724156 OA
    B. Paaßen, B. Mokbel, and B. Hammer, “Adaptive structure metrics for automated feedback provision in Java programming”, Proceedings of the ESANN, 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, M. Verleysen, ed., 2015, pp.307-312.
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  • [35]
    2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2762087
    B. Paaßen, B. Mokbel, and B. Hammer, “A Toolbox for Adaptive Sequence Dissimilarity Measures for Intelligent Tutoring Systems”, Proceedings of the 8th International Conference on Educational Data Mining, O.C. Santos, et al., eds., International Educational Datamining Society, 2015, pp.632-632.
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  • [34]
    2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2752955 OA
    O. Walter, et al., “Autonomous Learning of Representations”, KI - Künstliche Intelligenz, vol. 29, 2015, pp. 339–351.
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  • [33]
    2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2783369 OA
    B. Mokbel and A. Schulz, “Towards Dimensionality Reduction for Smart Home Sensor Data”, Proceedings of the Workshop New Challenges in Neural Computation (NC² 2015), B. Hammer, T. Martinetz, and T. Villmann, eds., Machine Learning Reports, 2015, pp.41-48.
    PUB | PDF | Download (ext.)
     
  • [32]
    2014 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2982100
    S. Gross, et al., “How to Select an Example? A Comparison of Selection Strategies in Example-Based Learning”, Intelligent Tutoring Systems, S. Trausan-Matu, et al., eds., Lecture Notes in Computer Science, Cham: Springer International Publishing, 2014, pp.340-347.
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  • [31]
    2014 | Konferenzbeitrag | PUB-ID: 2909360
    S. Gross, et al., “How to Select an Example? A Comparison of Selection Strategies in Example-Based Learning”, Intelligent Tutoring Systems, S. Trausan-Matu, et al., eds., Lecture Notes in Computer Science, vol. 8474, Springer, 2014, pp.340-347.
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  • [30]
    2014 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2673554 OA
    B. Mokbel, B. Paaßen, and B. Hammer, “Adaptive distance measures for sequential data”, ESANN, 22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, M. Verleysen, ed., Bruges, Belgium: i6doc.com, 2014, pp.265-270.
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  • [29]
    2014 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2734058
    S. Gross, et al., “Example-based feedback provision using structured solution spaces”, International Journal of Learning Technology, vol. 9, 2014, pp. 248-280.
    PUB | DOI | Download (ext.)
     
  • [28]
    2014 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2710067 OA
    B. Mokbel, B. Paaßen, and B. Hammer, “Efficient Adaptation of Structure Metrics in Prototype-Based Classification”, Artificial Neural Networks and Machine Learning - ICANN 2014 - 24th International Conference on Artificial Neural Networks, Hamburg, Germany, September 15-19, 2014. Proceedings, S. Wermter, et al., eds., Lecture Notes in Computer Science, vol. 8681, Springer, 2014, pp.571-578.
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  • [27]
    2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2623500
    A. Gisbrecht, et al., “Nonlinear dimensionality reduction for cluster identification in metagenomic samples”, 17th International Conference on Information Visualisation IV 2013, E. Banissi, ed., Piscataway, NJ: IEEE, 2013, pp.174-179.
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  • [26]
    2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2625185
    B. Mokbel, et al., “Domain-Independent Proximity Measures in Intelligent Tutoring Systems”, Proceedings of the 6th International Conference on Educational Data Mining (EDM), S.K. D'Mello, R.A. Calvo, and A. Olney, eds., 2013, pp.334-335.
    PUB | Download (ext.)
     
  • [25]
    2013 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2612736
    B. Mokbel, et al., “Visualizing the quality of dimensionality reduction”, Neurocomputing, vol. 112, 2013, pp. 109-123.
    PUB | DOI | WoS
     
  • [24]
    2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2670686
    S. Gross, et al., “Towards a Domain-Independent ITS Middleware Architecture”, 2013 IEEE 13th International Conference on Advanced Learning Technologies, IEEE, 2013, pp.408-409.
    PUB | DOI | WoS
     
  • [23]
    2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2625207
    S. Gross, et al., “Towards Providing Feedback to Students in Absence of Formalized Domain Models”, AIED, 2013, pp.644-648.
    PUB
     
  • [22]
    2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982108
    A. Gisbrecht, B. Mokbel, and B. Hammer, “Linear basis-function t-SNE for fast nonlinear dimensionality reduction”, The 2012 International Joint Conference on Neural Networks (IJCNN), IEEE, 2012, pp.1-8.
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  • [21]
    2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2625232
    A. Gisbrecht, et al., “Linear Time Relational Prototype Based Learning”, International Journal of Neural Systems, vol. 22, 2012, : 1250021.
    PUB | DOI | WoS | PubMed | Europe PMC
     
  • [20]
    2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2625260
    A. Gisbrecht, et al., “Out-of-sample kernel extensions for nonparametric dimensionality reduction”, ESANN 2012, 2012, pp.531-536.
    PUB
     
  • [19]
    2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2536426 OA
    B. Mokbel, et al., “How to Quantitatively Compare Data Dissimilarities for Unsupervised Machine Learning?”, Artificial Neural Networks in Pattern Recognition. 5th INNS IAPR TC 3 GIRPR Workshop, ANNPR 2012. Proceedings, N. Mana, F. Schwenker, and E. Trentin, eds., Lecture Notes in Artificial Intelligence, vol. 7477, Springer Berlin Heidelberg, 2012, pp.1-13.
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  • [18]
    2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2625276
    A. Gisbrecht, B. Mokbel, and B. Hammer, “Linear Basis-Function t-SNE for Fast Nonlinear Dimensionality Reduction”, IJCNN, 2012.
    PUB
     
  • [17]
    2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2625242
    S. Gross, et al., “Feedback Provision Strategies in Intelligent Tutoring Systems Based on Clustered Solution Spaces”, DeLFI, 2012, pp.27-38.
    PUB
     
  • [16]
    2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2536444 OA
    S. Gross, et al., “Feedback Provision Strategies in Intelligent Tutoring Systems Based on Clustered Solution Spaces”, DeLFI 2012: Die 10. e-Learning Fachtagung Informatik, J. Desel, et al., eds., GI-Edition : Proceedings, vol. 207, Hagen, Germany: Köllen, 2012, pp.27-38.
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  • [15]
    2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534877
    F.-M. Schleif, et al., “Learning Relevant Time Points for Time-Series Data in the Life Sciences”, ICANN (2), Lecture Notes in Computer Science, vol. 7553, Berlin, Heidelberg: Springer Berlin Heidelberg, 2012, pp.531-539.
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  • [14]
    2012 | Konferenzbeitrag | PUB-ID: 2909356
    B. Mokbel, et al., “Visualizing the quality of dimensionality reduction”, ESANN 2012, M. Verleysen, ed., 2012, pp.179--184.
    PUB
     
  • [13]
    2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534868
    B. Hammer, et al., “White Box Classification of Dissimilarity Data”, HAIS (1), Berlin, Heidelberg: Springer Berlin Heidelberg, 2012, pp.309-321.
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  • [12]
    2011 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2982113
    B. Hammer, et al., “Topographic Mapping of Dissimilarity Data”, Advances in Self-Organizing Maps, J. Laaksonen and T. Honkela, eds., Lecture Notes in Computer Science, Berlin, Heidelberg: Springer Berlin Heidelberg, 2011, pp.1-15.
    PUB | DOI
     
  • [11]
    2011 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2982111
    B. Hammer, et al., “Prototype-Based Classification of Dissimilarity Data”, Advances in Intelligent Data Analysis X, J. Gama, E. Bradley, and J. Hollmén, eds., Lecture Notes in Computer Science, Berlin, Heidelberg: Springer Berlin Heidelberg, 2011, pp.185-197.
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  • [10]
    2011 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2982109
    B. Hammer, et al., “A General Framework for Dimensionality Reduction for Large Data Sets”, Advances in Self-Organizing Maps, J. Laaksonen and T. Honkela, eds., Lecture Notes in Computer Science, Berlin, Heidelberg: Springer Berlin Heidelberg, 2011, pp.277-287.
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  • [9]
    2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276485
    B. Hammer, et al., “Topographic Mapping of Dissimilarity Data”, WSOM'11, 2011.
    PUB
     
  • [8]
    2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276512
    B. Hammer, et al., “A general framework for dimensionality reduction for large data sets”, WSOM'11, 2011.
    PUB
     
  • [7]
    2011 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2276531
    A. Gisbrecht, B. Mokbel, and B. Hammer, “Relational Generative Topographic Mapping”, Neurocomputing, vol. 74, 2011, pp. 1359-1371.
    PUB | DOI | WoS
     
  • [6]
    2010 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2982117
    A. Gisbrecht, et al., “Visualizing Dissimilarity Data Using Generative Topographic Mapping”, KI 2010: Advances in Artificial Intelligence, R. Dillmann, et al., eds., Lecture Notes in Computer Science, Berlin, Heidelberg: Springer Berlin Heidelberg, 2010, pp.227-237.
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  • [5]
    2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276543
    A. Gisbrecht, B. Mokbel, and B. Hammer, “The Nystrom approximation for relational generative topographic mappings”, NIPS workshop on challenges of Data Visualization, 2010.
    PUB
     
  • [4]
    2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276547
    B. Mokbel, A. Gisbrecht, and B. Hammer, “On the effect of clustering on quality assessment measures for dimensionality reduction”, NIPS workshop on Challenges of Data Visualization, 2010.
    PUB
     
  • [3]
    2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993452
    A. Gisbrecht, B. Mokbel, and B. Hammer, “Relational Generative Topographic Map”, ESANN'10, M. Verleysen, ed., Evere: D side, 2010, pp.277-282.
    PUB
     
  • [2]
    2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993457
    A. Gisbrecht, et al., “Visualizing Dissimilarity Data using generative topographic mapping”, KI'2010, R. Dillmann, et al., eds., 2010, pp.227-237.
    PUB
     
  • [1]
    2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993835
    B. Mokbel, A. Hasenfuss, and B. Hammer, “Graph-based Representation of Symbolic Musical Data”, Graph-Based Representation in Pattern Recognition (GbRPR 2009). Lecture Notes in Computer Science, 5534, A. Torsello, et al., eds., Lecture notes in computer science, vol. 5534, Berlin: Springer, 2009, pp.42-51.
    PUB | DOI
     
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