69 Publikationen
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2024 | Zeitschriftenaufsatz | PUB-ID: 2987814Morgenroth, Thekla, Begeny, Christopher T., Kirby, Teri A., Paaßen, Benjamin, and Zeng, Yangzhe. 2024. “Dissecting Whiteness: consistencies and differences in the stereotypes of lower- and upper-class White US Americans”. Self and Identity, 1-25.
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2023 | Preprint | Veröffentlicht | PUB-ID: 2980970Strotherm, Janine, Müller, Alissa, Hammer, Barbara, and Paaßen, Benjamin. 2023. “Fairness in KI-Systemen”.
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2022 | Konferenzbeitrag | PUB-ID: 2979001Paaßen, Benjamin, Dywel, Malwina, Fleckenstein, Melanie, and Pinkwart, Niels. 2022. “Sparse Factor Autoencoders for Item Response Theory”. In Proceedings of the 15th International Conference on Educational Data Mining (EDM 2022), ed. Alexandra I. Cristea, Chris Brown, Tanja Mitrovic, and Nigel Bosch, 17–26.
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2022 | Zeitschriftenaufsatz | PUB-ID: 2978970Paaßen, Benjamin, Koprinska, Irena, and Yacef, Kalina. 2022. “Recursive Tree Grammar Autoencoders”. Machine Learning 111: 3393–3423.
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2022 | Zeitschriftenaufsatz | PUB-ID: 2979004Paaßen, Benjamin, Dehne, Julian, Krishnaraja, Swathi, Kovalkov, Anastasia, Gal, Kobi, and Pinkwart, Niels. 2022. “A conceptual graph-based model of creativity in learning”. Frontiers in Education 7.
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2022 | Konferenzbeitrag | PUB-ID: 2979003Paaßen, Benjamin, Baumgartner, Tobias, Geisen, Mai, Riedl, Nina, and Kravčík, Miloš. 2022. “Few-shot Keypose Detection for Learning of Psychomotor Skills”. In 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, 22–27.
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2022 | Konferenzbeitrag | PUB-ID: 2979002Paaßen, Benjamin, Dywel, Malwina, Fleckenstein, Melanie, and Pinkwart, Niels. 2022. “Interpretable Knowledge Gain Prediction for Vocational Preparatory E-Learnings”. In 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, 132–137.
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2022 | Konferenzbeitrag | PUB-ID: 2979000Paaßen, Benjamin, Göpfert, Christina, and Pinkwart, Niels. 2022. “Faster Confidence Intervals for Item Response Theory via an Approximate Likelihood”. In Proceedings of the 15th International Conference on Educational Data Mining (EDM 2022), ed. Alexandra I. Cristea, Chris Brown, Tanja Mitrovic, and Nigel Bosch, 555–559.
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2022 | Konferenzbeitrag | PUB-ID: 2978999Picones, Gio, Paaßen, Benjamin, Koprinska, Irena, and Yacef, Kalina. 2022. “Combining domain modelling and student modelling techniques in a single pipeline to support task-sequencing”. In Proceedings of the 15th International Conference on Educational Data Mining (EDM 2022), ed. Alexandra I. Cristea, Chris Brown, Tanja Mitrovic, and Nigel Bosch, 217–227.
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2022 | Zeitschriftenaufsatz | PUB-ID: 2978998Paaßen, Benjamin, Schulz, Alexander, C. Stewart, Terrence, and Hammer, Barbara. 2022. “Reservoir Memory Machines as Neural Computers”. IEEE Transactions on Neural Networks and Learning Systems 33 (6): 2575–2585.
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2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2978969Paaßen, Benjamin, McBroom, Jessica, Jeffries, Bryn, Koprinska, Irena, and Yacef, Kalina. 2021. “Mapping Python Programs to Vectors using Recursive Neural Encodings”. Journal of Educational Datamining 13 (3): 1–35.
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2021 | Zeitschriftenaufsatz | PUB-ID: 2978997Kovalkov, Anastasia, Paaßen, Benjamin, Segal, Avi, Pinkwart, Niels, and Gal, Kobi. 2021. “Automatic Creativity Measurement in Scratch Programs Across Modalities”. IEEE Transactions on Learning Technologies 14 (6): 740–753.
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2021 | Konferenzbeitrag | PUB-ID: 2978996Bacciu, Davide, Bianchi, Filippo Maria, Paaßen, Benjamin, and Alippi, Cesare. 2021. “Deep learning for graphs”. In {Proceedings of the 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2021)}, ed. Michel Verleysen, 89–98.
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2021 | Konferenzbeitrag | PUB-ID: 2978995Paaßen, Benjamin, and Kravčík, Miloš. 2021. “Teaching psychomotor skills using machine learning for error detection”. In Proceedings of the 1st International Workshop on Multimodal Immersive Learning Systems ({MILeS} 2021), ed. Roland Klemke and Khaleel Asyraaf Mat Sanusi, 8–14.
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2021 | Konferenzbeitrag | PUB-ID: 2978967Paaßen, Benjamin. 2021. “An A*-algorithm for the Unordered Tree Edit Distance with Custom Costs”. In 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, 364–371. Springer.
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2021 | Konferenzbeitrag | PUB-ID: 2978966Kovalkov, Anastasia, Paaßen, Benjamin, Segal, Avi, Gal, Kobi, and Pinkwart, Niels. 2021. “Modeling Creativity in Visual Programming: From Theory to Practice”. In 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.
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2021 | Konferenzbeitrag | PUB-ID: 2978965Paaßen, Benjamin, Bertsch, Andreas, Langer-Fischer, Katharina, Rüdian, Sylvio, Wang, Xia, Sinha, Rupali, Kuzilek, Jakub, Britsch, Stefan, and Pinkwart, Niels. 2021. “Analyzing Student Success and Mistakes in Virtual Microscope Structure Search Tasks”. In 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.
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2021 | Konferenzbeitrag | PUB-ID: 2978964McBroom, Jessica, Paaßen, Benjamin, Jeffries, Bryn, Koprinska, Irena, and Yacef, Kalina. 2021. “Progress Networks as a Tool for Analysing Student Programming Difficulties”. In Proceedings of the Twenty-Third Australasian Computing Education Conference (ACE '21), ed. Claudia Szabo and Judy Sheard, 158–167. Association for Computing Machinery.
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2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2954542Paaßen, Benjamin, Schulz, Alexander, and Hammer, Barbara. 2021. “Reservoir Stack Machines”. Neurocomputing 470: 352-364.
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2020 | Konferenzbeitrag | PUB-ID: 2978963Paaßen, Benjamin, Koprinska, Irena, and Yacef, Kalina. 2020. “Tree Echo State Autoencoders with Grammars”. In Proceedings of the 2020 International Joint Conference on Neural Networks ({IJCNN} 2020), ed. Asim Roy, 1–8.
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2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2941931Paaßen, Benjamin, and Schulz, Alexander. 2020. “Reservoir memory machines”. In Proceedings of the 28th European Symposium on Artificial Neural Networks (ESANN 2020), ed. Michel Verleysen, 567-572. Bruges: i6doc.
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2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2944191Morgenroth, Thekla, Stratemeyer, Michelle, and Paaßen, Benjamin. 2020. “The Gendered Nature and Malleability of Gamer Stereotypes”. Cyberpsychology, Behavior, and Social Networking 23 (8): 557-561.
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2019 | Monographie | PUB-ID: 2935200Paaßen, Benjamin, Artelt, André, and Hammer, Barbara. 2019. Lecture Notes on Applied Optimization. Faculty of Technology, Bielefeld University.
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2019 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2934458Prahm, Cosima, Schulz, Alexander, Paaßen, Benjamin, Schoisswohl, Johannes, Kaniusas, Eugenius, Dorffner, Georg, Hammer, Barbara, and Aszmann, Oskar. 2019. “Counteracting Electrode Shifts in Upper-Limb Prosthesis Control via Transfer Learning”. IEEE Transactions on Neural Systems and Rehabilitation Engineering 27 (5): 956-962.
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2019 | Datenpublikation | PUB-ID: 2941052Paaßen, Benjamin. 2019. Python Programming Dataset. Bielefeld University.
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2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2937053Paaßen, Benjamin. 2019. “Adversarial Edit Attacks for Tree Data”. In Proceedings of the 20th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2019), ed. Hujun Yin, David Camacho, and Peter Tino, 11871:359-366. Lecture Notes in Computer Science. Cham: Springer.
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2019 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2935953Price, Thomas W., Dong, Yihuan, Zhi, Rui, Paaßen, Benjamin, Lytle, Nicholas, Cateté, Veronica, and Barnes, Tiffany. 2019. “A Comparison of the Quality of Data-Driven Programming Hint Generation Algorithms”. International Journal of Artificial Intelligence in Education 29 (3): 368-395.
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2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2933502Paaßen, Benjamin, Bunge, Astrid, Hainke, Carolin, Sindelar, Leon, and Vogelsang, Matthias. 2019. “Dynamic fairness - Breaking vicious cycles in automatic decision making”. In Proceedings of the 27th European Symposium on Artificial Neural Networks (ESANN 2019), ed. Michel Verleysen, 477-482. Louvain-la-Neuve: i6doc.
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2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2934571Paaßen, Benjamin, Gallicchio, Claudio, Micheli, Alessio, and Sperduti, Alessandro. 2019. “Embeddings and Representation Learning for Structured Data”. In Proceedings of the 27th European Symposium on Artificial Neural Networks (ESANN 2019), ed. Michel Verleysen, 85-94.
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2018 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2911900Paaßen, Benjamin, Göpfert, Christina, and Hammer, Barbara. 2018. “Time Series Prediction for Graphs in Kernel and Dissimilarity Spaces”. Neural Processing Letters 48 (2): 669-689.
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2018 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2914505Paaßen, Benjamin, Schulz, Alexander, Hahne, Janne, and Hammer, Barbara. 2018. “Expectation maximization transfer learning and its application for bionic hand prostheses”. Neurocomputing 298: 122-133.
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2018 | Datenpublikation | PUB-ID: 2916863Paaßen, Benjamin, and Ahmaro, Aya. 2018. VBB Shortest Path Data 2018. Bielefeld University.
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2018 | Datenpublikation | PUB-ID: 2919994Paaßen, Benjamin. 2018. Tree Edit Distance Learning via Adaptive Symbol Embeddings. Bielefeld University.
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2018 | Datenpublikation | PUB-ID: 2916990Paaßen, Benjamin. 2018. Median Generalized Learning Vector Quantization for Distance Data. Bielefeld University.
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2018 | Datenpublikation | PUB-ID: 2916980Paaßen, Benjamin. 2018. Relational Neural Gas. Bielefeld University.
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2018 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2913389Paaßen, Benjamin, Hammer, Barbara, Price, Thomas, Barnes, Tiffany, Gross, Sebastian, and Pinkwart, Niels. 2018. “The Continuous Hint Factory - Providing Hints in Vast and Sparsely Populated Edit Distance Spaces”. Journal of Educational Data Mining 10 (1): 1-35.
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2018 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2919844Paaßen, Benjamin, Gallicchio, Claudio, Micheli, Alessio, and Hammer, Barbara. 2018. “Tree Edit Distance Learning via Adaptive Symbol Embeddings”. In Proceedings of the 35th International Conference on Machine Learning (ICML 2018), ed. Jennifer Dy and Andreas Krause, 80:3973-3982. Proceedings of Machine Learning Research.
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2018 | Preprint | Entwurf | PUB-ID: 2919918Paaßen, Benjamin. Draft. “Revisiting the tree edit distance and its backtracing: A tutorial”. arXiv:1805.06869.
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2017 | Datenpublikation | PUB-ID: 2913104Paaßen, Benjamin. 2017. Time Series Prediction for Relational and Kernel Data. Bielefeld University.
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2017 | Datenpublikation | PUB-ID: 2912671Paaßen, Benjamin, and Schulz, Alexander. 2017. Linear Supervised Transfer Learning Toolbox. Bielefeld University.
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2017 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2909369Paaßen, Benjamin, Schulz, Alexander, Hahne, Janne, and Hammer, Barbara. 2017. “An EM transfer learning algorithm with applications in bionic hand prostheses”. In Proceedings of the 25th European Symposium on Artificial Neural Networks (ESANN 2017), ed. Michel Verleysen, 129-134. Bruges: i6doc.com.
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2017 | Kurzbeitrag Konferenz / Poster | Veröffentlicht | PUB-ID: 2914663Paaßen, Benjamin. 2017. “Two or three things we do (not) know about distances”. In Proceedings of the Ninth Mittweida Workshop on Computational Intelligence (MiWoCI 2017), ed. Frank-Michael Schleif and Thomas Villmann, 32-33. Machine Learning Reports.
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2017 | Datenpublikation | PUB-ID: 2913083Paaßen, Benjamin. 2017. BinaryAdder UML Dataset. Bielefeld University.
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2017 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2909037Prahm, Cosima, Schulz, Alexander, Paaßen, Benjamin, Aszmann, Oskar, Hammer, Barbara, and Dorffner, Georg. 2017. “Echo State Networks as Novel Approach for Low-Cost Myoelectric Control”. In Proceedings of the 16th Conference on Artificial Intelligence in Medicine (AIME 2017), ed. Annette ten Telje, Christian Popow, John H. Holmes, and Lucia Sacchi, 10259:338--342. Lecture Notes in Computer Science. Springer.
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2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2909367Kummert, Johannes, Paaßen, Benjamin, Jensen, Joris, Göpfert, Christina, and Hammer, Barbara. 2016. “Local Reject Option for Deterministic Multi-class SVM”. In 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, 9887:251--258. Lecture Notes in Computer Science. Cham: Springer Nature.
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2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2900676Paaßen, Benjamin, Göpfert, Christina, and Hammer, Barbara. 2016. “Gaussian process prediction for time series of structured data”. In Proceedings of the ESANN, 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ed. Michele Verleysen, 41--46. Louvain-la-Neuve: Ciaco - i6doc.com.
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2016 | Datenpublikation | PUB-ID: 2900684Paaßen, Benjamin. 2016. Java Sorting Programs. Bielefeld University.
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2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2904509Paaßen, Benjamin, Jensen, Joris, and Hammer, Barbara. 2016. “Execution Traces as a Powerful Data Representation for Intelligent Tutoring Systems for Programming”. In Proceedings of the 9th International Conference on Educational Data Mining, ed. Tiffany Barnes, Min Chi, and Mingyu Feng, 183-190. Raleigh, North Carolina, USA: International Educational Datamining Society.
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2016 | Datenpublikation | PUB-ID: 2900666Paaßen, Benjamin. 2016. MiniPalindrome. Bielefeld University.
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2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2905729Göpfert, Christina, Paaßen, Benjamin, and Hammer, Barbara. 2016. “Convergence of Multi-pass Large Margin Nearest Neighbor Metric Learning”. In 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, 9887:510-517. Lecture Notes in Computer Science. Cham: Springer Nature.
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2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2905855Paaßen, Benjamin, Schulz, Alexander, and Hammer, Barbara. 2016. “Linear Supervised Transfer Learning for Generalized Matrix LVQ”. In Proceedings of the Workshop New Challenges in Neural Computation 2016, ed. Barbara Hammer, Thomas Martinetz, and Thomas Villmann, 11-18. Machine Learning Reports.
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2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2904178Prahm, Cosima, Paaßen, Benjamin, Schulz, Alexander, Hammer, Barbara, and Aszmann, Oskar. 2016. “Transfer Learning for Rapid Re-calibration of a Myoelectric Prosthesis after Electrode Shift”. In 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, 153--157. Springer.
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2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2710031Mokbel, Bassam, Paaßen, Benjamin, Schleif, Frank-Michael, and Hammer, Barbara. 2015. “Metric learning for sequences in relational LVQ”. Neurocomputing 169 (SI): 306-322.
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2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2724156Paaßen, Benjamin, Mokbel, Bassam, and Hammer, Barbara. 2015. “Adaptive structure metrics for automated feedback provision in Java programming”. In Proceedings of the ESANN, 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ed. Michel Verleysen, 307-312.
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2015 | Report | PUB-ID: 2712107Stöckel, Andreas, Paaßen, Benjamin, Dickfelder, Raphael, Göpfert, Jan Philip, Brazda, Nicole, Müller, Hans Werner, Cimiano, Philipp, Hartung, Matthias, and Klinger, Roman. 2015. SCIE: Information Extraction for Spinal Cord Injury Preclinical Experiments – A Webservice and Open Source Toolkit. bioRxive.org.
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2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2762087Paaßen, Benjamin, Mokbel, Bassam, and Hammer, Barbara. 2015. “A Toolbox for Adaptive Sequence Dissimilarity Measures for Intelligent Tutoring Systems”. In 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, et al., 632-632. International Educational Datamining Society.
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2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2752955Walter, Oliver, Häb-Umbach, Reinhold, Mokbel, Bassam, Paaßen, Benjamin, and Hammer, Barbara. 2015. “Autonomous Learning of Representations”. KI - Künstliche Intelligenz 29 (4): 339–351.
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2014 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2678214Hofmann, Daniela, Schleif, Frank-Michael, Paaßen, Benjamin, and Hammer, Barbara. 2014. “Learning interpretable kernelized prototype-based models”. Neurocomputing 141: 84-96.
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2014 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2673554Mokbel, Bassam, Paaßen, Benjamin, and Hammer, Barbara. 2014. “Adaptive distance measures for sequential data”. In ESANN, 22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ed. Michel Verleysen, 265-270. Bruges, Belgium: i6doc.com.
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2014 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2683760Paaßen, Benjamin, Stöckel, Andreas, Dickfelder, Raphael, Göpfert, Jan Philip, Brazda, Nicole, Kirchhoffer, Tarek, Müller, Hans Werner, Klinger, Roman, Hartung, Matthias, and Cimiano, Philipp. 2014. “Ontology-based Extraction of Structured Information from Publications on Preclinical Experiments for Spinal Cord Injury Treatments”. In 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, 25-32. Dublin, Ireland.
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2014 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2734058Gross, Sebastian, Mokbel, Bassam, Paaßen, Benjamin, Hammer, Barbara, and Pinkwart, Niels. 2014. “Example-based feedback provision using structured solution spaces”. International Journal of Learning Technology 9 (3): 248-280.
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2014 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2710067Mokbel, Bassam, Paaßen, Benjamin, and Hammer, Barbara. 2014. “Efficient Adaptation of Structure Metrics in Prototype-Based Classification”. In 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, 8681:571-578. Lecture Notes in Computer Science. Springer.
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2013 | Datenpublikation | PUB-ID: 2692491Paaßen, Benjamin. 2013. VBB Midi Dataset. Bielefeld University.
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2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2625185Mokbel, Bassam, Gross, Sebastian, Paaßen, Benjamin, Pinkwart, Niels, and Hammer, Barbara. 2013. “Domain-Independent Proximity Measures in Intelligent Tutoring Systems”. In Proceedings of the 6th International Conference on Educational Data Mining (EDM), ed. S. K. D'Mello, R. A. Calvo, and A. Olney, 334-335.