39 Publikationen

Alle markieren

[39]
2018 | Zeitschriftenaufsatz | PUB-ID: 2911900
Paaßen B, Göpfert C, Hammer B. Time Series Prediction for Graphs in Kernel and Dissimilarity Spaces. Neural Processing Letters. 2018;48(2):669-689.
PUB | DOI | Download (ext.) | arXiv
 
[38]
2018 | Datenpublikation | PUB-ID: 2916980
Paaßen B. (2018): Relational Neural Gas. Bielefeld University. doi:10.4119/unibi/2916980.
PUB | Dateien verfügbar | DOI
 
[37]
2018 | Zeitschriftenaufsatz | PUB-ID: 2913389
Paaßen B, Hammer B, Price T, Barnes T, Gross S, Pinkwart N. The Continuous Hint Factory - Providing Hints in Vast and Sparsely Populated Edit Distance Spaces. Journal of Educational Data Mining. 2018;10(1):1-35.
PUB | Download (ext.) | arXiv
 
[36]
2018 | Konferenzbeitrag | PUB-ID: 2919844
Paaßen B, Gallicchio C, Micheli A, Hammer B. Tree Edit Distance Learning via Adaptive Symbol Embeddings. In: Dy J, Krause A, eds. Proceedings of the 35th International Conference on Machine Learning (ICML 2018). Proceedings of Machine Learning Research. Vol 80. 2018: 3973-3982.
PUB | Download (ext.) | arXiv
 
[35]
2018 | Datenpublikation | PUB-ID: 2916990
Paaßen B. (2018): Median Generalized Learning Vector Quantization for Distance Data. Bielefeld University. doi:10.4119/unibi/2916990.
PUB | Dateien verfügbar | DOI
 
[34]
2018 | Datenpublikation | PUB-ID: 2916863
Paaßen B, Ahmaro A. (2018): VBB Shortest Path Data 2018. Bielefeld University. doi:10.4119/unibi/2916863.
PUB | Dateien verfügbar | DOI
 
[33]
2018 | Konferenzbeitrag | PUB-ID: 2916318
Berger K, Schulz A, Paaßen B, Hammer B. Linear Supervised Transfer Learning for the Large Margin Nearest Neighbor Classifier. Presented at the SSCI CIDM 2017.
PUB | DOI
 
[32]
2018 | Preprint | PUB-ID: 2919918
Paaßen B. Revisiting the tree edit distance and its backtracing: A tutorial. arXiv:1805.06869. Draft.
PUB | Download (ext.) | arXiv
 
[31]
2018 | Datenpublikation | PUB-ID: 2919994
Paaßen B. (2018): Tree Edit Distance Learning via Adaptive Symbol Embeddings. Bielefeld University. doi:10.4119/unibi/2919994.
PUB | Dateien verfügbar | DOI
 
[30]
2018 | Zeitschriftenaufsatz | PUB-ID: 2914505
Paaßen B, Schulz A, Hahne J, Hammer B. Expectation maximization transfer learning and its application for bionic hand prostheses. Neurocomputing. 2018;298:122-133.
PUB | DOI | Download (ext.) | WoS | arXiv
 
[29]
2017 | Datenpublikation | PUB-ID: 2913104
Paaßen B. Time Series Prediction for Relational and Kernel Data. Bielefeld University; 2017.
PUB | Dateien verfügbar | DOI
 
[28]
2017 | Konferenzbeitrag | PUB-ID: 2909369
Paaßen B, Schulz A, Hahne J, Hammer B. An EM transfer learning algorithm with applications in bionic hand prostheses. In: Verleysen M, ed. Proceedings of the 25th European Symposium on Artificial Neural Networks (ESANN 2017). Bruges: i6doc.com; 2017: 129-134.
PUB | PDF
 
[27]
2017 | Datenpublikation | PUB-ID: 2912671
Paaßen B, Schulz A. (2017): Linear Supervised Transfer Learning Toolbox. Bielefeld University. doi:10.4119/unibi/2912671.
PUB | Dateien verfügbar | DOI
 
[26]
2017 | Datenpublikation | PUB-ID: 2913083
Paaßen B. (2017): BinaryAdder UML Dataset. Bielefeld University. doi:10.4119/unibi/2913083.
PUB | Dateien verfügbar | DOI
 
[25]
2017 | Zeitschriftenaufsatz | PUB-ID: 2905302
Paaßen B, Morgenroth T, Stratemeyer M. What is a True Gamer? The Male Gamer Stereotype and the Marginalization of Women in Video Game Culture. Sex Roles. 2017;76(7-8):421-435.
PUB | PDF | DOI | WoS
 
[24]
2017 | Konferenzbeitrag | PUB-ID: 2909037
Prahm C, Schulz A, Paaßen B, Aszmann O, Hammer B, Dorffner G. Echo State Networks as Novel Approach for Low-Cost Myoelectric Control. In: ten Telje A, Popow C, Holmes JH, Sacchi L, eds. Proceedings of the 16th Conference on Artificial Intelligence in Medicine (AIME 2017). Lecture Notes in Computer Science. Vol 10259. Springer; 2017: 338--342.
PUB | Dateien verfügbar | DOI
 
[23]
2017 | Kurzbeitrag Konferenz | PUB-ID: 2914663
Paaßen B. Two or three things we do (not) know about distances. In: Schleif F-M, Villmann T, eds. Proceedings of the Ninth Mittweida Workshop on Computational Intelligence (MiWoCI 2017). Machine Learning Reports. 2017: 32-33.
PUB | PDF | Download (ext.)
 
[22]
2016 | Konferenzbeitrag | PUB-ID: 2900676
Paaßen B, Göpfert C, Hammer B. Gaussian process prediction for time series of structured data. In: Verleysen M, ed. Proceedings of the ESANN, 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Louvain-la-Neuve: Ciaco - i6doc.com; 2016: 41--46.
PUB | PDF
 
[21]
2016 | Konferenzbeitrag | PUB-ID: 2905729
Göpfert C, Paaßen B, Hammer B. Convergence of Multi-pass Large Margin Nearest Neighbor Metric Learning. In: E.P. Villa A, Masulli P, Pons Rivero AJ, eds. Artificial Neural Networks and Machine Learning – ICANN 2016: 25th International Conference on Artificial Neural Networks, Barcelona, Spain, September 6-9, 2016, Proceedings, Part II. Lecture Notes in Computer Science. Vol 9887. Cham: Springer Nature; 2016: 510-517.
PUB | PDF | DOI
 
[20]
2016 | Konferenzbeitrag | PUB-ID: 2909367
Kummert J, Paaßen B, Jensen J, Göpfert C, Hammer B. Local Reject Option for Deterministic Multi-class SVM. In: E.P. Villa A, Masulli P, Pons Rivero AJ, eds. Artificial Neural Networks and Machine Learning - ICANN 2016 - 25th International Conference on Artificial Neural Networks, Barcelona, Spain, September 6-9, 2016, Proceedings, Part II. Lecture Notes in Computer Science. Vol 9887. Cham: Springer Nature; 2016: 251--258.
PUB | DOI
 
[19]
2016 | Konferenzbeitrag | PUB-ID: 2905855
Paaßen B, Schulz A, Hammer B. Linear Supervised Transfer Learning for Generalized Matrix LVQ. In: Hammer B, Martinetz T, Villmann T, eds. Proceedings of the Workshop New Challenges in Neural Computation 2016. Machine Learning Reports. 2016: 11-18.
PUB | Download (ext.)
 
[18]
2016 | Konferenzbeitrag | PUB-ID: 2904509
Paaßen B, Jensen J, Hammer B. Execution Traces as a Powerful Data Representation for Intelligent Tutoring Systems for Programming. In: Barnes T, Chi M, Feng M, eds. Proceedings of the 9th International Conference on Educational Data Mining. Raleigh, North Carolina, USA: International Educational Datamining Society; 2016: 183-190.
PUB | Download (ext.)
 
[17]
2016 | Datenpublikation | PUB-ID: 2900666
Paaßen B. (2016): MiniPalindrome. Bielefeld University. doi:10.4119/unibi/2900666.
PUB | Dateien verfügbar | DOI
 
[16]
2016 | Datenpublikation | PUB-ID: 2900684
Paaßen B. (2016): Java Sorting Programs. Bielefeld University. doi:10.4119/unibi/2900684.
PUB | Dateien verfügbar | DOI
 
[15]
2016 | Zeitschriftenaufsatz | PUB-ID: 2783224
Paaßen B, Mokbel B, Hammer B. Adaptive structure metrics for automated feedback provision in intelligent tutoring systems. Neurocomputing. 2016;192(SI):3-13.
PUB | PDF | DOI | WoS
 
[14]
2016 | Konferenzbeitrag | PUB-ID: 2904178
Prahm C, Paaßen B, Schulz A, Hammer B, Aszmann O. Transfer Learning for Rapid Re-calibration of a Myoelectric Prosthesis after Electrode Shift. In: Ibáñez J, Gonzáles-Vargas J, Azorín JM, Akay M, Pons JL, eds. Converging Clinical and Engineering Research on Neurorehabilitation II: Proceedings of the 3rd International Conference on NeuroRehabilitation (ICNR2016). Springer; 2016: 153--157.
PUB | PDF | DOI | Download (ext.)
 
[13]
2015 | Report | PUB-ID: 2712107
Stöckel A, Paaßen B, Dickfelder R, et al. SCIE: Information Extraction for Spinal Cord Injury Preclinical Experiments – A Webservice and Open Source Toolkit. bioRxive.org; 2015.
PUB | PDF | DOI | Download (ext.)
 
[12]
2015 | Konferenzbeitrag | PUB-ID: 2762087
Paaßen B, Mokbel B, Hammer B. A Toolbox for Adaptive Sequence Dissimilarity Measures for Intelligent Tutoring Systems. In: Santos OC, Boticario JG, Romero C, et al., eds. Proceedings of the 8th International Conference on Educational Data Mining. International Educational Datamining Society; 2015: 632-632.
PUB | Download (ext.)
 
[11]
2015 | Zeitschriftenaufsatz | PUB-ID: 2752955
Walter O, Häb-Umbach R, Mokbel B, Paaßen B, Hammer B. Autonomous Learning of Representations. KI - Künstliche Intelligenz. 2015;29(4):339–351.
PUB | PDF | DOI | Download (ext.) | WoS
 
[10]
2015 | Konferenzbeitrag | PUB-ID: 2724156
Paaßen B, Mokbel B, Hammer B. Adaptive structure metrics for automated feedback provision in Java programming. In: Verleysen M, ed. Proceedings of the ESANN, 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. 2015: 307-312.
PUB | PDF
 
[9]
2015 | Bielefelder Masterarbeit | PUB-ID: 2736686
Paaßen B. Adaptive Affine Sequence Alignment Using Algebraic Dynamic Programming. Bielefeld: Bielefeld University; 2015.
PUB | PDF
 
[8]
2015 | Zeitschriftenaufsatz | PUB-ID: 2710031
Mokbel B, Paaßen B, Schleif F-M, Hammer B. Metric learning for sequences in relational LVQ. Neurocomputing. 2015;169(SI):306-322.
PUB | PDF | DOI | Download (ext.) | WoS
 
[7]
2014 | Zeitschriftenaufsatz | PUB-ID: 2678214
Hofmann D, Schleif F-M, Paaßen B, Hammer B. Learning interpretable kernelized prototype-based models. Neurocomputing. 2014;141:84-96.
PUB | DOI | Download (ext.) | WoS
 
[6]
2014 | Konferenzbeitrag | PUB-ID: 2673554
Mokbel B, Paaßen B, Hammer B. Adaptive distance measures for sequential data. In: Verleysen M, ed. ESANN, 22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges, Belgium: i6doc.com; 2014: 265-270.
PUB | PDF
 
[5]
2014 | Konferenzbeitrag | PUB-ID: 2683760
Paaßen B, Stöckel A, Dickfelder R, et al. Ontology-based Extraction of Structured Information from Publications on Preclinical Experiments for Spinal Cord Injury Treatments. In: Maynard D, Erp van M, Davis B, eds. Third Workshop on Semantic Web and Information Extraction (SWAIE). The 25th International Conference on Computational Linguistics (COLING). Dublin, Ireland; 2014: 25-32.
PUB | PDF | Download (ext.)
 
[4]
2014 | Zeitschriftenaufsatz | PUB-ID: 2734058
Gross S, Mokbel B, Paaßen B, Hammer B, Pinkwart N. Example-based feedback provision using structured solution spaces. International Journal of Learning Technology. 2014;9(3):248-280.
PUB | DOI | Download (ext.)
 
[3]
2014 | Konferenzbeitrag | PUB-ID: 2710067
Mokbel B, Paaßen B, Hammer B. Efficient Adaptation of Structure Metrics in Prototype-Based Classification. In: Wermter S, Weber C, Duch W, et al., eds. Artificial Neural Networks and Machine Learning - ICANN 2014 - 24th International Conference on Artificial Neural Networks, Hamburg, Germany, September 15-19, 2014. Proceedings. Lecture Notes in Computer Science. Vol 8681. Springer; 2014: 571-578.
PUB | PDF | DOI | Download (ext.)
 
[2]
2013 | Konferenzbeitrag | PUB-ID: 2625185
Mokbel B, Gross S, Paaßen B, Pinkwart N, Hammer B. Domain-Independent Proximity Measures in Intelligent Tutoring Systems. In: D'Mello SK, Calvo RA, Olney A, eds. Proceedings of the 6th International Conference on Educational Data Mining (EDM). 2013: 334-335.
PUB | Download (ext.)
 
[1]
2013 | Datenpublikation | PUB-ID: 2692491
Paaßen B. (2013): VBB Midi Dataset. Bielefeld University. doi:10.4119/unibi/2692491.
PUB | Dateien verfügbar | DOI
 

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Publikationen filtern

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Zitationsstil: ama

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39 Publikationen

Alle markieren

[39]
2018 | Zeitschriftenaufsatz | PUB-ID: 2911900
Paaßen B, Göpfert C, Hammer B. Time Series Prediction for Graphs in Kernel and Dissimilarity Spaces. Neural Processing Letters. 2018;48(2):669-689.
PUB | DOI | Download (ext.) | arXiv
 
[38]
2018 | Datenpublikation | PUB-ID: 2916980
Paaßen B. (2018): Relational Neural Gas. Bielefeld University. doi:10.4119/unibi/2916980.
PUB | Dateien verfügbar | DOI
 
[37]
2018 | Zeitschriftenaufsatz | PUB-ID: 2913389
Paaßen B, Hammer B, Price T, Barnes T, Gross S, Pinkwart N. The Continuous Hint Factory - Providing Hints in Vast and Sparsely Populated Edit Distance Spaces. Journal of Educational Data Mining. 2018;10(1):1-35.
PUB | Download (ext.) | arXiv
 
[36]
2018 | Konferenzbeitrag | PUB-ID: 2919844
Paaßen B, Gallicchio C, Micheli A, Hammer B. Tree Edit Distance Learning via Adaptive Symbol Embeddings. In: Dy J, Krause A, eds. Proceedings of the 35th International Conference on Machine Learning (ICML 2018). Proceedings of Machine Learning Research. Vol 80. 2018: 3973-3982.
PUB | Download (ext.) | arXiv
 
[35]
2018 | Datenpublikation | PUB-ID: 2916990
Paaßen B. (2018): Median Generalized Learning Vector Quantization for Distance Data. Bielefeld University. doi:10.4119/unibi/2916990.
PUB | Dateien verfügbar | DOI
 
[34]
2018 | Datenpublikation | PUB-ID: 2916863
Paaßen B, Ahmaro A. (2018): VBB Shortest Path Data 2018. Bielefeld University. doi:10.4119/unibi/2916863.
PUB | Dateien verfügbar | DOI
 
[33]
2018 | Konferenzbeitrag | PUB-ID: 2916318
Berger K, Schulz A, Paaßen B, Hammer B. Linear Supervised Transfer Learning for the Large Margin Nearest Neighbor Classifier. Presented at the SSCI CIDM 2017.
PUB | DOI
 
[32]
2018 | Preprint | PUB-ID: 2919918
Paaßen B. Revisiting the tree edit distance and its backtracing: A tutorial. arXiv:1805.06869. Draft.
PUB | Download (ext.) | arXiv
 
[31]
2018 | Datenpublikation | PUB-ID: 2919994
Paaßen B. (2018): Tree Edit Distance Learning via Adaptive Symbol Embeddings. Bielefeld University. doi:10.4119/unibi/2919994.
PUB | Dateien verfügbar | DOI
 
[30]
2018 | Zeitschriftenaufsatz | PUB-ID: 2914505
Paaßen B, Schulz A, Hahne J, Hammer B. Expectation maximization transfer learning and its application for bionic hand prostheses. Neurocomputing. 2018;298:122-133.
PUB | DOI | Download (ext.) | WoS | arXiv
 
[29]
2017 | Datenpublikation | PUB-ID: 2913104
Paaßen B. Time Series Prediction for Relational and Kernel Data. Bielefeld University; 2017.
PUB | Dateien verfügbar | DOI
 
[28]
2017 | Konferenzbeitrag | PUB-ID: 2909369
Paaßen B, Schulz A, Hahne J, Hammer B. An EM transfer learning algorithm with applications in bionic hand prostheses. In: Verleysen M, ed. Proceedings of the 25th European Symposium on Artificial Neural Networks (ESANN 2017). Bruges: i6doc.com; 2017: 129-134.
PUB | PDF
 
[27]
2017 | Datenpublikation | PUB-ID: 2912671
Paaßen B, Schulz A. (2017): Linear Supervised Transfer Learning Toolbox. Bielefeld University. doi:10.4119/unibi/2912671.
PUB | Dateien verfügbar | DOI
 
[26]
2017 | Datenpublikation | PUB-ID: 2913083
Paaßen B. (2017): BinaryAdder UML Dataset. Bielefeld University. doi:10.4119/unibi/2913083.
PUB | Dateien verfügbar | DOI
 
[25]
2017 | Zeitschriftenaufsatz | PUB-ID: 2905302
Paaßen B, Morgenroth T, Stratemeyer M. What is a True Gamer? The Male Gamer Stereotype and the Marginalization of Women in Video Game Culture. Sex Roles. 2017;76(7-8):421-435.
PUB | PDF | DOI | WoS
 
[24]
2017 | Konferenzbeitrag | PUB-ID: 2909037
Prahm C, Schulz A, Paaßen B, Aszmann O, Hammer B, Dorffner G. Echo State Networks as Novel Approach for Low-Cost Myoelectric Control. In: ten Telje A, Popow C, Holmes JH, Sacchi L, eds. Proceedings of the 16th Conference on Artificial Intelligence in Medicine (AIME 2017). Lecture Notes in Computer Science. Vol 10259. Springer; 2017: 338--342.
PUB | Dateien verfügbar | DOI
 
[23]
2017 | Kurzbeitrag Konferenz | PUB-ID: 2914663
Paaßen B. Two or three things we do (not) know about distances. In: Schleif F-M, Villmann T, eds. Proceedings of the Ninth Mittweida Workshop on Computational Intelligence (MiWoCI 2017). Machine Learning Reports. 2017: 32-33.
PUB | PDF | Download (ext.)
 
[22]
2016 | Konferenzbeitrag | PUB-ID: 2900676
Paaßen B, Göpfert C, Hammer B. Gaussian process prediction for time series of structured data. In: Verleysen M, ed. Proceedings of the ESANN, 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Louvain-la-Neuve: Ciaco - i6doc.com; 2016: 41--46.
PUB | PDF
 
[21]
2016 | Konferenzbeitrag | PUB-ID: 2905729
Göpfert C, Paaßen B, Hammer B. Convergence of Multi-pass Large Margin Nearest Neighbor Metric Learning. In: E.P. Villa A, Masulli P, Pons Rivero AJ, eds. Artificial Neural Networks and Machine Learning – ICANN 2016: 25th International Conference on Artificial Neural Networks, Barcelona, Spain, September 6-9, 2016, Proceedings, Part II. Lecture Notes in Computer Science. Vol 9887. Cham: Springer Nature; 2016: 510-517.
PUB | PDF | DOI
 
[20]
2016 | Konferenzbeitrag | PUB-ID: 2909367
Kummert J, Paaßen B, Jensen J, Göpfert C, Hammer B. Local Reject Option for Deterministic Multi-class SVM. In: E.P. Villa A, Masulli P, Pons Rivero AJ, eds. Artificial Neural Networks and Machine Learning - ICANN 2016 - 25th International Conference on Artificial Neural Networks, Barcelona, Spain, September 6-9, 2016, Proceedings, Part II. Lecture Notes in Computer Science. Vol 9887. Cham: Springer Nature; 2016: 251--258.
PUB | DOI
 
[19]
2016 | Konferenzbeitrag | PUB-ID: 2905855
Paaßen B, Schulz A, Hammer B. Linear Supervised Transfer Learning for Generalized Matrix LVQ. In: Hammer B, Martinetz T, Villmann T, eds. Proceedings of the Workshop New Challenges in Neural Computation 2016. Machine Learning Reports. 2016: 11-18.
PUB | Download (ext.)
 
[18]
2016 | Konferenzbeitrag | PUB-ID: 2904509
Paaßen B, Jensen J, Hammer B. Execution Traces as a Powerful Data Representation for Intelligent Tutoring Systems for Programming. In: Barnes T, Chi M, Feng M, eds. Proceedings of the 9th International Conference on Educational Data Mining. Raleigh, North Carolina, USA: International Educational Datamining Society; 2016: 183-190.
PUB | Download (ext.)
 
[17]
2016 | Datenpublikation | PUB-ID: 2900666
Paaßen B. (2016): MiniPalindrome. Bielefeld University. doi:10.4119/unibi/2900666.
PUB | Dateien verfügbar | DOI
 
[16]
2016 | Datenpublikation | PUB-ID: 2900684
Paaßen B. (2016): Java Sorting Programs. Bielefeld University. doi:10.4119/unibi/2900684.
PUB | Dateien verfügbar | DOI
 
[15]
2016 | Zeitschriftenaufsatz | PUB-ID: 2783224
Paaßen B, Mokbel B, Hammer B. Adaptive structure metrics for automated feedback provision in intelligent tutoring systems. Neurocomputing. 2016;192(SI):3-13.
PUB | PDF | DOI | WoS
 
[14]
2016 | Konferenzbeitrag | PUB-ID: 2904178
Prahm C, Paaßen B, Schulz A, Hammer B, Aszmann O. Transfer Learning for Rapid Re-calibration of a Myoelectric Prosthesis after Electrode Shift. In: Ibáñez J, Gonzáles-Vargas J, Azorín JM, Akay M, Pons JL, eds. Converging Clinical and Engineering Research on Neurorehabilitation II: Proceedings of the 3rd International Conference on NeuroRehabilitation (ICNR2016). Springer; 2016: 153--157.
PUB | PDF | DOI | Download (ext.)
 
[13]
2015 | Report | PUB-ID: 2712107
Stöckel A, Paaßen B, Dickfelder R, et al. SCIE: Information Extraction for Spinal Cord Injury Preclinical Experiments – A Webservice and Open Source Toolkit. bioRxive.org; 2015.
PUB | PDF | DOI | Download (ext.)
 
[12]
2015 | Konferenzbeitrag | PUB-ID: 2762087
Paaßen B, Mokbel B, Hammer B. A Toolbox for Adaptive Sequence Dissimilarity Measures for Intelligent Tutoring Systems. In: Santos OC, Boticario JG, Romero C, et al., eds. Proceedings of the 8th International Conference on Educational Data Mining. International Educational Datamining Society; 2015: 632-632.
PUB | Download (ext.)
 
[11]
2015 | Zeitschriftenaufsatz | PUB-ID: 2752955
Walter O, Häb-Umbach R, Mokbel B, Paaßen B, Hammer B. Autonomous Learning of Representations. KI - Künstliche Intelligenz. 2015;29(4):339–351.
PUB | PDF | DOI | Download (ext.) | WoS
 
[10]
2015 | Konferenzbeitrag | PUB-ID: 2724156
Paaßen B, Mokbel B, Hammer B. Adaptive structure metrics for automated feedback provision in Java programming. In: Verleysen M, ed. Proceedings of the ESANN, 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. 2015: 307-312.
PUB | PDF
 
[9]
2015 | Bielefelder Masterarbeit | PUB-ID: 2736686
Paaßen B. Adaptive Affine Sequence Alignment Using Algebraic Dynamic Programming. Bielefeld: Bielefeld University; 2015.
PUB | PDF
 
[8]
2015 | Zeitschriftenaufsatz | PUB-ID: 2710031
Mokbel B, Paaßen B, Schleif F-M, Hammer B. Metric learning for sequences in relational LVQ. Neurocomputing. 2015;169(SI):306-322.
PUB | PDF | DOI | Download (ext.) | WoS
 
[7]
2014 | Zeitschriftenaufsatz | PUB-ID: 2678214
Hofmann D, Schleif F-M, Paaßen B, Hammer B. Learning interpretable kernelized prototype-based models. Neurocomputing. 2014;141:84-96.
PUB | DOI | Download (ext.) | WoS
 
[6]
2014 | Konferenzbeitrag | PUB-ID: 2673554
Mokbel B, Paaßen B, Hammer B. Adaptive distance measures for sequential data. In: Verleysen M, ed. ESANN, 22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges, Belgium: i6doc.com; 2014: 265-270.
PUB | PDF
 
[5]
2014 | Konferenzbeitrag | PUB-ID: 2683760
Paaßen B, Stöckel A, Dickfelder R, et al. Ontology-based Extraction of Structured Information from Publications on Preclinical Experiments for Spinal Cord Injury Treatments. In: Maynard D, Erp van M, Davis B, eds. Third Workshop on Semantic Web and Information Extraction (SWAIE). The 25th International Conference on Computational Linguistics (COLING). Dublin, Ireland; 2014: 25-32.
PUB | PDF | Download (ext.)
 
[4]
2014 | Zeitschriftenaufsatz | PUB-ID: 2734058
Gross S, Mokbel B, Paaßen B, Hammer B, Pinkwart N. Example-based feedback provision using structured solution spaces. International Journal of Learning Technology. 2014;9(3):248-280.
PUB | DOI | Download (ext.)
 
[3]
2014 | Konferenzbeitrag | PUB-ID: 2710067
Mokbel B, Paaßen B, Hammer B. Efficient Adaptation of Structure Metrics in Prototype-Based Classification. In: Wermter S, Weber C, Duch W, et al., eds. Artificial Neural Networks and Machine Learning - ICANN 2014 - 24th International Conference on Artificial Neural Networks, Hamburg, Germany, September 15-19, 2014. Proceedings. Lecture Notes in Computer Science. Vol 8681. Springer; 2014: 571-578.
PUB | PDF | DOI | Download (ext.)
 
[2]
2013 | Konferenzbeitrag | PUB-ID: 2625185
Mokbel B, Gross S, Paaßen B, Pinkwart N, Hammer B. Domain-Independent Proximity Measures in Intelligent Tutoring Systems. In: D'Mello SK, Calvo RA, Olney A, eds. Proceedings of the 6th International Conference on Educational Data Mining (EDM). 2013: 334-335.
PUB | Download (ext.)
 
[1]
2013 | Datenpublikation | PUB-ID: 2692491
Paaßen B. (2013): VBB Midi Dataset. Bielefeld University. doi:10.4119/unibi/2692491.
PUB | Dateien verfügbar | DOI
 

Suche

Publikationen filtern

Darstellung / Sortierung

Zitationsstil: ama

Export / Einbettung