69 Publikationen

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  • [69]
    2024 | Zeitschriftenaufsatz | PUB-ID: 2987814
    Morgenroth, Thekla, Begeny, Christopher T., Kirby, Teri A., Paaßen, Benjamin, and Zeng, Yangzhe. “Dissecting Whiteness: consistencies and differences in the stereotypes of lower- and upper-class White US Americans”. Self and Identity (2024): 1-25.
    PUB | DOI | WoS
     
  • [68]
    2023 | Preprint | Veröffentlicht | PUB-ID: 2980970
    Strotherm, Janine, Müller, Alissa, Hammer, Barbara, and Paaßen, Benjamin. “Fairness in KI-Systemen”. (2023).
    PUB | Download (ext.) | arXiv
     
  • [67]
    2022 | Konferenzbeitrag | PUB-ID: 2979001
    Paaßen, Benjamin, Dywel, Malwina, Fleckenstein, Melanie, and Pinkwart, Niels. “Sparse Factor Autoencoders for Item Response Theory”. Proceedings of the 15th International Conference on Educational Data Mining (EDM 2022). Ed. Alexandra I. Cristea, Chris Brown, Tanja Mitrovic, and Nigel Bosch. 2022. 17–26.
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  • [66]
    2022 | Zeitschriftenaufsatz | PUB-ID: 2978970 OA
    Paaßen, Benjamin, Koprinska, Irena, and Yacef, Kalina. “Recursive Tree Grammar Autoencoders”. Machine Learning 111 (2022): 3393–3423.
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  • [65]
    2022 | Zeitschriftenaufsatz | PUB-ID: 2979004 OA
    Paaßen, Benjamin, Dehne, Julian, Krishnaraja, Swathi, Kovalkov, Anastasia, Gal, Kobi, and Pinkwart, Niels. “A conceptual graph-based model of creativity in learning”. Frontiers in Education 7 (2022).
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  • [64]
    2022 | Konferenzbeitrag | PUB-ID: 2979003
    Paaßen, Benjamin, Baumgartner, Tobias, Geisen, Mai, Riedl, Nina, and Kravčík, Miloš. “Few-shot Keypose Detection for Learning of Psychomotor Skills”. Proceedings of the Second International Workshop on Multimodal Immersive Learning Systems ({MILeS} 2022). Ed. Khaleel Asyraaf Mat Sanusi, Bibeg Limbu, Jan Schneider, Daniele Di Mitri, and Roland Klemke. 2022. 22–27.
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  • [63]
    2022 | Konferenzbeitrag | PUB-ID: 2979002
    Paaßen, Benjamin, Dywel, Malwina, Fleckenstein, Melanie, and Pinkwart, Niels. “Interpretable Knowledge Gain Prediction for Vocational Preparatory E-Learnings”. Proceedings of the 23rd International Conference on Artificial Intelligence in Education (AIED 2022) Practitioner’s Track. Ed. Jeanine Antoinette DeFalco, Diego Dermeval Medeiros da Cunha Matos, Berit Blanc, and Insa Reichow. 2022. 132–137.
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  • [62]
    2022 | Konferenzbeitrag | PUB-ID: 2979000
    Paaßen, Benjamin, Göpfert, Christina, and Pinkwart, Niels. “Faster Confidence Intervals for Item Response Theory via an Approximate Likelihood”. Proceedings of the 15th International Conference on Educational Data Mining (EDM 2022). Ed. Alexandra I. Cristea, Chris Brown, Tanja Mitrovic, and Nigel Bosch. 2022. 555–559.
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  • [61]
    2022 | Konferenzbeitrag | PUB-ID: 2978999
    Picones, Gio, Paaßen, Benjamin, Koprinska, Irena, and Yacef, Kalina. “Combining domain modelling and student modelling techniques in a single pipeline to support task-sequencing”. Proceedings of the 15th International Conference on Educational Data Mining (EDM 2022). Ed. Alexandra I. Cristea, Chris Brown, Tanja Mitrovic, and Nigel Bosch. 2022. 217–227.
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  • [60]
    2022 | Zeitschriftenaufsatz | PUB-ID: 2978998
    Paaßen, Benjamin, Schulz, Alexander, C. Stewart, Terrence, and Hammer, Barbara. “Reservoir Memory Machines as Neural Computers”. IEEE Transactions on Neural Networks and Learning Systems 33.6 (2022): 2575–2585.
    PUB | DOI | Download (ext.) | arXiv
     
  • [59]
    2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2978969
    Paaßen, Benjamin, McBroom, Jessica, Jeffries, Bryn, Koprinska, Irena, and Yacef, Kalina. “Mapping Python Programs to Vectors using Recursive Neural Encodings”. Journal of Educational Datamining 13.3 (2021): 1–35.
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  • [58]
    2021 | Zeitschriftenaufsatz | PUB-ID: 2978997
    Kovalkov, Anastasia, Paaßen, Benjamin, Segal, Avi, Pinkwart, Niels, and Gal, Kobi. “Automatic Creativity Measurement in Scratch Programs Across Modalities”. IEEE Transactions on Learning Technologies 14.6 (2021): 740–753.
    PUB | DOI | Download (ext.) | arXiv
     
  • [57]
    2021 | Konferenzbeitrag | PUB-ID: 2978996
    Bacciu, Davide, Bianchi, Filippo Maria, Paaßen, Benjamin, and Alippi, Cesare. “Deep learning for graphs”. {Proceedings of the 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2021)}. Ed. Michel Verleysen. 2021. 89–98.
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  • [56]
    2021 | Konferenzbeitrag | PUB-ID: 2978995
    Paaßen, Benjamin, and Kravčík, Miloš. “Teaching psychomotor skills using machine learning for error detection”. Proceedings of the 1st International Workshop on Multimodal Immersive Learning Systems ({MILeS} 2021). Ed. Roland Klemke and Khaleel Asyraaf Mat Sanusi. 2021. 8–14.
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  • [55]
    2021 | Konferenzbeitrag | PUB-ID: 2978967
    Paaßen, Benjamin. “An A*-algorithm for the Unordered Tree Edit Distance with Custom Costs”. Proceedings of the 14th International Conference on Similarity Search and Applications (SISAP 2021). Ed. Nora Reyes, Richard Connor, Nils Kriege, Daniyal Kazempour, Ilaria Bartolini, Erich Schubert, and Jian-Jia Chen. Springer, 2021. 364–371.
    PUB | DOI | Download (ext.) | arXiv
     
  • [54]
    2021 | Konferenzbeitrag | PUB-ID: 2978966
    Kovalkov, Anastasia, Paaßen, Benjamin, Segal, Avi, Gal, Kobi, and Pinkwart, Niels. “Modeling Creativity in Visual Programming: From Theory to Practice”. Proceedings of the 15th {International Conference on Educational Data Mining} ({EDM} 2021). Ed. François Bouchet, Jill-Jênn Vie, Sharon Hsiao, and Sherry Sahebi. International Educational Datamining Society, 2021.
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  • [53]
    2021 | Konferenzbeitrag | PUB-ID: 2978965
    Paaßen, Benjamin, Bertsch, Andreas, Langer-Fischer, Katharina, Rüdian, Sylvio, Wang, Xia, Sinha, Rupali, Kuzilek, Jakub, Britsch, Stefan, and Pinkwart, Niels. “Analyzing Student Success and Mistakes in Virtual Microscope Structure Search Tasks”. Proceedings of the 15th {International Conference on Educational Data Mining} ({EDM} 2021). Ed. François Bouchet, Jill-Jênn Vie, Sharon Hsiao, and Sherry Sahebi. International Educational Datamining Society, 2021.
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  • [52]
    2021 | Konferenzbeitrag | PUB-ID: 2978964
    McBroom, Jessica, Paaßen, Benjamin, Jeffries, Bryn, Koprinska, Irena, and Yacef, Kalina. “Progress Networks as a Tool for Analysing Student Programming Difficulties”. Proceedings of the Twenty-Third Australasian Computing Education Conference (ACE '21). Ed. Claudia Szabo and Judy Sheard. Association for Computing Machinery, 2021. 158–167.
    PUB | DOI
     
  • [51]
    2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2954542
    Paaßen, Benjamin, Schulz, Alexander, and Hammer, Barbara. “Reservoir Stack Machines”. Neurocomputing 470 (2021): 352-364.
    PUB | DOI | Download (ext.) | WoS | arXiv
     
  • [50]
    2020 | Konferenzbeitrag | PUB-ID: 2978963
    Paaßen, Benjamin, Koprinska, Irena, and Yacef, Kalina. “Tree Echo State Autoencoders with Grammars”. Proceedings of the 2020 International Joint Conference on Neural Networks ({IJCNN} 2020). Ed. Asim Roy. 2020. 1–8.
    PUB | DOI | Download (ext.) | arXiv
     
  • [49]
    2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2941931
    Paaßen, Benjamin, and Schulz, Alexander. “Reservoir memory machines”. Proceedings of the 28th European Symposium on Artificial Neural Networks (ESANN 2020). Ed. Michel Verleysen. Bruges: i6doc, 2020. 567-572.
    PUB | Download (ext.) | arXiv
     
  • [48]
    2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2944191
    Morgenroth, Thekla, Stratemeyer, Michelle, and Paaßen, Benjamin. “The Gendered Nature and Malleability of Gamer Stereotypes”. Cyberpsychology, Behavior, and Social Networking 23.8 (2020): 557-561.
    PUB | DOI | WoS | PubMed | Europe PMC
     
  • [47]
    2019 | Monographie | PUB-ID: 2935200 OA
    Paaßen, Benjamin, Artelt, André, and Hammer, Barbara. Lecture Notes on Applied Optimization. Faculty of Technology, Bielefeld University, 2019.
    PUB | Dateien verfügbar
     
  • [46]
    2019 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2934458 OA
    Prahm, Cosima, Schulz, Alexander, Paaßen, Benjamin, Schoisswohl, Johannes, Kaniusas, Eugenius, Dorffner, Georg, Hammer, Barbara, and Aszmann, Oskar. “Counteracting Electrode Shifts in Upper-Limb Prosthesis Control via Transfer Learning”. IEEE Transactions on Neural Systems and Rehabilitation Engineering 27.5 (2019): 956-962.
    PUB | PDF | DOI | WoS | PubMed | Europe PMC
     
  • [45]
    2019 | Datenpublikation | PUB-ID: 2941052 OA
    Paaßen, Benjamin. Python Programming Dataset. Bielefeld University, 2019.
    PUB | Dateien verfügbar | DOI
     
  • [44]
    2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2937053
    Paaßen, Benjamin. “Adversarial Edit Attacks for Tree Data”. Proceedings of the 20th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2019). Ed. Hujun Yin, David Camacho, and Peter Tino. Cham: Springer, 2019.Vol. 11871. Lecture Notes in Computer Science. 359-366.
    PUB | DOI | Download (ext.) | arXiv
     
  • [43]
    2019 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2935953
    Price, Thomas W., Dong, Yihuan, Zhi, Rui, Paaßen, Benjamin, Lytle, Nicholas, Cateté, Veronica, and Barnes, Tiffany. “A Comparison of the Quality of Data-Driven Programming Hint Generation Algorithms”. International Journal of Artificial Intelligence in Education 29.3 (2019): 368-395.
    PUB | DOI | WoS
     
  • [42]
    2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2933502
    Paaßen, Benjamin, Bunge, Astrid, Hainke, Carolin, Sindelar, Leon, and Vogelsang, Matthias. “Dynamic fairness - Breaking vicious cycles in automatic decision making”. Proceedings of the 27th European Symposium on Artificial Neural Networks (ESANN 2019). Ed. Michel Verleysen. Louvain-la-Neuve: i6doc, 2019. 477-482.
    PUB | Download (ext.) | arXiv
     
  • [41]
    2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2934571
    Paaßen, Benjamin, Gallicchio, Claudio, Micheli, Alessio, and Sperduti, Alessandro. “Embeddings and Representation Learning for Structured Data”. Proceedings of the 27th European Symposium on Artificial Neural Networks (ESANN 2019). Ed. Michel Verleysen. 2019. 85-94.
    PUB | Download (ext.) | arXiv
     
  • [40]
    2019 | Bielefelder E-Dissertation | PUB-ID: 2935545 OA
    Paaßen, Benjamin. Metric Learning for Structured Data. Bielefeld: Universität Bielefeld, 2019.
    PUB | PDF | DOI
     
  • [39]
    2018 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2911900
    Paaßen, Benjamin, Göpfert, Christina, and Hammer, Barbara. “Time Series Prediction for Graphs in Kernel and Dissimilarity Spaces”. Neural Processing Letters 48.2 (2018): 669-689.
    PUB | DOI | Download (ext.) | WoS | arXiv
     
  • [38]
    2018 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2914505
    Paaßen, Benjamin, Schulz, Alexander, Hahne, Janne, and Hammer, Barbara. “Expectation maximization transfer learning and its application for bionic hand prostheses”. Neurocomputing 298 (2018): 122-133.
    PUB | DOI | Download (ext.) | WoS | arXiv
     
  • [37]
    2018 | Datenpublikation | PUB-ID: 2916863 OA
    Paaßen, Benjamin, and Ahmaro, Aya. VBB Shortest Path Data 2018. Bielefeld University, 2018.
    PUB | Dateien verfügbar | DOI
     
  • [36]
    2018 | Datenpublikation | PUB-ID: 2919994 OA
    Paaßen, Benjamin. Tree Edit Distance Learning via Adaptive Symbol Embeddings. Bielefeld University, 2018.
    PUB | Dateien verfügbar | DOI
     
  • [35]
    2018 | Datenpublikation | PUB-ID: 2916990 OA
    Paaßen, Benjamin. Median Generalized Learning Vector Quantization for Distance Data. Bielefeld University, 2018.
    PUB | Dateien verfügbar | DOI
     
  • [34]
    2018 | Datenpublikation | PUB-ID: 2916980 OA
    Paaßen, Benjamin. Relational Neural Gas. Bielefeld University, 2018.
    PUB | Dateien verfügbar | DOI
     
  • [33]
    2018 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2913389
    Paaßen, Benjamin, Hammer, Barbara, Price, Thomas, Barnes, Tiffany, Gross, Sebastian, and Pinkwart, Niels. “The Continuous Hint Factory - Providing Hints in Vast and Sparsely Populated Edit Distance Spaces”. Journal of Educational Data Mining 10.1 (2018): 1-35.
    PUB | Download (ext.) | arXiv
     
  • [32]
    2018 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2919844
    Paaßen, Benjamin, Gallicchio, Claudio, Micheli, Alessio, and Hammer, Barbara. “Tree Edit Distance Learning via Adaptive Symbol Embeddings”. Proceedings of the 35th International Conference on Machine Learning (ICML 2018). Ed. Jennifer Dy and Andreas Krause. 2018.Vol. 80. Proceedings of Machine Learning Research. 3973-3982.
    PUB | Download (ext.) | arXiv
     
  • [31]
    2018 | Konferenzbeitrag | PUB-ID: 2916318
    Berger, Kolja, Schulz, Alexander, Paaßen, Benjamin, and Hammer, Barbara. “Linear Supervised Transfer Learning for the Large Margin Nearest Neighbor Classifier”. Presented at the SSCI CIDM 2017, 2018.
    PUB | DOI
     
  • [30]
    2018 | Preprint | Entwurf | PUB-ID: 2919918
    Paaßen, Benjamin. “Revisiting the tree edit distance and its backtracing: A tutorial”. arXiv:1805.06869 (Draft).
    PUB | Download (ext.) | arXiv
     
  • [29]
    2017 | Datenpublikation | PUB-ID: 2913104 OA
    Paaßen, Benjamin. Time Series Prediction for Relational and Kernel Data. Bielefeld University, 2017.
    PUB | Dateien verfügbar | DOI
     
  • [28]
    2017 | Datenpublikation | PUB-ID: 2912671 OA
    Paaßen, Benjamin, and Schulz, Alexander. Linear Supervised Transfer Learning Toolbox. Bielefeld University, 2017.
    PUB | Dateien verfügbar | DOI
     
  • [27]
    2017 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2909369 OA
    Paaßen, Benjamin, Schulz, Alexander, Hahne, Janne, and Hammer, Barbara. “An EM transfer learning algorithm with applications in bionic hand prostheses”. Proceedings of the 25th European Symposium on Artificial Neural Networks (ESANN 2017). Ed. Michel Verleysen. Bruges: i6doc.com, 2017. 129-134.
    PUB | PDF
     
  • [26]
    2017 | Kurzbeitrag Konferenz / Poster | Veröffentlicht | PUB-ID: 2914663 OA
    Paaßen, Benjamin. “Two or three things we do (not) know about distances”. Proceedings of the Ninth Mittweida Workshop on Computational Intelligence (MiWoCI 2017). Ed. Frank-Michael Schleif and Thomas Villmann. 2017. Machine Learning Reports. 32-33.
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  • [25]
    2017 | Datenpublikation | PUB-ID: 2913083 OA
    Paaßen, Benjamin. BinaryAdder UML Dataset. Bielefeld University, 2017.
    PUB | Dateien verfügbar | DOI
     
  • [24]
    2017 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2905302 OA
    Paaßen, Benjamin, Morgenroth, Thekla, and Stratemeyer, Michelle. “What is a True Gamer? The Male Gamer Stereotype and the Marginalization of Women in Video Game Culture”. Sex Roles 76.7-8 (2017): 421-435.
    PUB | PDF | DOI | WoS
     
  • [23]
    2017 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2909037 OA
    Prahm, Cosima, Schulz, Alexander, Paaßen, Benjamin, Aszmann, Oskar, Hammer, Barbara, and Dorffner, Georg. “Echo State Networks as Novel Approach for Low-Cost Myoelectric Control”. Proceedings of the 16th Conference on Artificial Intelligence in Medicine (AIME 2017). Ed. Annette ten Telje, Christian Popow, John H. Holmes, and Lucia Sacchi. Springer, 2017.Vol. 10259. Lecture Notes in Computer Science. 338--342.
    PUB | Dateien verfügbar | DOI
     
  • [22]
    2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2909367
    Kummert, Johannes, Paaßen, Benjamin, Jensen, Joris, Göpfert, Christina, and Hammer, Barbara. “Local Reject Option for Deterministic Multi-class SVM”. Artificial Neural Networks and Machine Learning - ICANN 2016 - 25th International Conference on Artificial Neural Networks, Barcelona, Spain, September 6-9, 2016, Proceedings, Part II. Ed. Alessandro E.P. Villa, Paolo Masulli, and Antonio Javier Pons Rivero. Cham: Springer Nature, 2016.Vol. 9887. Lecture Notes in Computer Science. 251--258.
    PUB | DOI
     
  • [21]
    2016 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2783224 OA
    Paaßen, Benjamin, Mokbel, Bassam, and Hammer, Barbara. “Adaptive structure metrics for automated feedback provision in intelligent tutoring systems”. Neurocomputing 192.SI (2016): 3-13.
    PUB | PDF | DOI | WoS
     
  • [20]
    2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2900676 OA
    Paaßen, Benjamin, Göpfert, Christina, and Hammer, Barbara. “Gaussian process prediction for time series of structured data”. Proceedings of the ESANN, 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Ed. Michele Verleysen. Louvain-la-Neuve: Ciaco - i6doc.com, 2016. 41--46.
    PUB | PDF
     
  • [19]
    2016 | Datenpublikation | PUB-ID: 2900684 OA
    Paaßen, Benjamin. Java Sorting Programs. Bielefeld University, 2016.
    PUB | Dateien verfügbar | DOI
     
  • [18]
    2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2904509
    Paaßen, Benjamin, Jensen, Joris, and Hammer, Barbara. “Execution Traces as a Powerful Data Representation for Intelligent Tutoring Systems for Programming”. Proceedings of the 9th International Conference on Educational Data Mining. Ed. Tiffany Barnes, Min Chi, and Mingyu Feng. Raleigh, North Carolina, USA: International Educational Datamining Society, 2016. 183-190.
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  • [17]
    2016 | Datenpublikation | PUB-ID: 2900666 OA
    Paaßen, Benjamin. MiniPalindrome. Bielefeld University, 2016.
    PUB | Dateien verfügbar | DOI
     
  • [16]
    2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2905729 OA
    Göpfert, Christina, Paaßen, Benjamin, and Hammer, Barbara. “Convergence of Multi-pass Large Margin Nearest Neighbor Metric Learning”. Artificial Neural Networks and Machine Learning – ICANN 2016: 25th International Conference on Artificial Neural Networks, Barcelona, Spain, September 6-9, 2016, Proceedings, Part II. Ed. Alessandro E.P. Villa, Paolo Masulli, and Antonio Javier Pons Rivero. Cham: Springer Nature, 2016.Vol. 9887. Lecture Notes in Computer Science. 510-517.
    PUB | PDF | DOI
     
  • [15]
    2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2905855
    Paaßen, Benjamin, Schulz, Alexander, and Hammer, Barbara. “Linear Supervised Transfer Learning for Generalized Matrix LVQ”. Proceedings of the Workshop New Challenges in Neural Computation 2016. Ed. Barbara Hammer, Thomas Martinetz, and Thomas Villmann. 2016. Machine Learning Reports. 11-18.
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  • [14]
    2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2904178 OA
    Prahm, Cosima, Paaßen, Benjamin, Schulz, Alexander, Hammer, Barbara, and Aszmann, Oskar. “Transfer Learning for Rapid Re-calibration of a Myoelectric Prosthesis after Electrode Shift”. Converging Clinical and Engineering Research on Neurorehabilitation II: Proceedings of the 3rd International Conference on NeuroRehabilitation (ICNR2016). Ed. Jaime Ibáñez, José Gonzáles-Vargas, José María Azorín, Metin Akay, and José Luis Pons. Springer, 2016. 153--157.
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  • [13]
    2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2710031 OA
    Mokbel, Bassam, Paaßen, Benjamin, Schleif, Frank-Michael, and Hammer, Barbara. “Metric learning for sequences in relational LVQ”. Neurocomputing 169.SI (2015): 306-322.
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  • [12]
    2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2724156 OA
    Paaßen, Benjamin, Mokbel, Bassam, and Hammer, Barbara. “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. Ed. Michel Verleysen. 2015. 307-312.
    PUB | PDF
     
  • [11]
    2015 | Report | PUB-ID: 2712107 OA
    Stöckel, Andreas, Paaßen, Benjamin, Dickfelder, Raphael, Göpfert, Jan Philip, Brazda, Nicole, Müller, Hans Werner, Cimiano, Philipp, Hartung, Matthias, and Klinger, Roman. SCIE: Information Extraction for Spinal Cord Injury Preclinical Experiments – A Webservice and Open Source Toolkit. bioRxive.org, 2015.
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  • [10]
    2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2762087
    Paaßen, Benjamin, Mokbel, Bassam, and Hammer, Barbara. “A Toolbox for Adaptive Sequence Dissimilarity Measures for Intelligent Tutoring Systems”. Proceedings of the 8th International Conference on Educational Data Mining. Ed. Olga Christina Santos, Jesus Gonzalez Boticario, Cristobal Romero, Mykola Pechenizkiy, Agathe Merceron, Piotr Mitros, Jose Maria Luna, Christian Mihaescu, Pablo Moreno, Arnon Hershkovitz, Sebastian Ventura, and Michel Desmarais. International Educational Datamining Society, 2015. 632-632.
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  • [9]
    2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2752955 OA
    Walter, Oliver, Häb-Umbach, Reinhold, Mokbel, Bassam, Paaßen, Benjamin, and Hammer, Barbara. “Autonomous Learning of Representations”. KI - Künstliche Intelligenz 29.4 (2015): 339–351.
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  • [8]
    2015 | Bielefelder Masterarbeit | PUB-ID: 2736686 OA
    Paaßen, Benjamin. Adaptive Affine Sequence Alignment Using Algebraic Dynamic Programming. Bielefeld: Bielefeld University, 2015.
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  • [7]
    2014 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2678214
    Hofmann, Daniela, Schleif, Frank-Michael, Paaßen, Benjamin, and Hammer, Barbara. “Learning interpretable kernelized prototype-based models”. Neurocomputing 141 (2014): 84-96.
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  • [6]
    2014 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2673554 OA
    Mokbel, Bassam, Paaßen, Benjamin, and Hammer, Barbara. “Adaptive distance measures for sequential data”. ESANN, 22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Ed. Michel Verleysen. Bruges, Belgium: i6doc.com, 2014. 265-270.
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  • [5]
    2014 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2683760 OA
    Paaßen, Benjamin, Stöckel, Andreas, Dickfelder, Raphael, Göpfert, Jan Philip, Brazda, Nicole, Kirchhoffer, Tarek, Müller, Hans Werner, Klinger, Roman, Hartung, Matthias, and Cimiano, Philipp. “Ontology-based Extraction of Structured Information from Publications on Preclinical Experiments for Spinal Cord Injury Treatments”. Third Workshop on Semantic Web and Information Extraction (SWAIE). The 25th International Conference on Computational Linguistics (COLING). Ed. Diana Maynard, Marieke Erp van, and Brian Davis. Dublin, Ireland, 2014. 25-32.
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  • [4]
    2014 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2734058
    Gross, Sebastian, Mokbel, Bassam, Paaßen, Benjamin, Hammer, Barbara, and Pinkwart, Niels. “Example-based feedback provision using structured solution spaces”. International Journal of Learning Technology 9.3 (2014): 248-280.
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  • [3]
    2014 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2710067 OA
    Mokbel, Bassam, Paaßen, Benjamin, and Hammer, Barbara. “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. Ed. Stefan Wermter, Cornelius Weber, Włodzisław Duch, Timo Honkela, Petia Koprinkova-Hristova, Sven Magg, Günther Palm, and Allessandro Villa. Springer, 2014.Vol. 8681. Lecture Notes in Computer Science. 571-578.
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  • [2]
    2013 | Datenpublikation | PUB-ID: 2692491 OA
    Paaßen, Benjamin. VBB Midi Dataset. Bielefeld University, 2013.
    PUB | Dateien verfügbar | DOI
     
  • [1]
    2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2625185
    Mokbel, Bassam, Gross, Sebastian, Paaßen, Benjamin, Pinkwart, Niels, and Hammer, Barbara. “Domain-Independent Proximity Measures in Intelligent Tutoring Systems”. Proceedings of the 6th International Conference on Educational Data Mining (EDM). Ed. S. K. D'Mello, R. A. Calvo, and A. Olney. 2013. 334-335.
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