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• [9]
  

  2024 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2989138

  O. Müller and C. Düsing, “Forecasting the Impact of Artificial Intelligence on the Labor Market Through Natural Language Processing of Job Posting”, SSRN Electronic Journal, 2024.

  PUB | DOI
   
• [8]
  

  2024 | Konferenzbeitrag | Angenommen | PUB-ID: 2989137

  F. Liedeker, et al., “An Empirical Investigation of Users' Assessment of XAI Explanations: Identifying the Sweet-Spot of Explanation Complexity”, Late-breaking work, Demos and Doctoral Consortium, colocated with The 2nd World Conference on eXplainable Artificial Intelligence, July 17-19, Valetta, Malta, Accepted.

  PUB
   
• [7]
  

  2024 | Konferenzbeitrag | Angenommen | PUB-ID: 2988518

  C. Düsing, et al., “Design of an Explainable Input Control for Cross-Company Federated Learning”, Presented at the 32nd European Conference on Information Systems, Paphos, Cyprus, Accepted.

  PUB
   
• [6]
  

  2024 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2986487

  C. Düsing and P. Cimiano, “Monitoring Concept Drift in Continuous Federated Learning Platforms”, International Symposium on Intelligent Data Analysis, Lecture Notes in Computer Science, 2024.

  PUB | DOI | Download (ext.)
   
• [5]
  

  2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2979412

  C. Düsing and P. Cimiano, “Federated Learning to Improve Counterfactual Explanations for Sepsis Treatment Prediction”, Artificial Intelligence in Medicine: 21st International Conference on Artificial Intelligence in Medicine, Lecture Notes in Computer Science , Springer Link, 2023.

  PUB | DOI | Download (ext.)
   
• [4]
  

  2022 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2967989

  C. Düsing and P. Cimiano, “On the Trade-off Between Benefit and Contribution for Clients in Federated Learning in Healthcare”, Proceedings of 21st IEEE International Conference on Machine Learning and Applications, 2022.

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

  2022 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2967988

  C. Düsing and P. Cimiano, “Towards predicting client benefit and contribution in federated learning from data imbalance”, CoNEXT '22: Proceedings of the 18th International Conference on emerging Networking EXperiments and Technologies, Association for Computing Machinery, ed., New York, NY, USA: ACM, 2022, pp.23-29.

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

  2022 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2960377

  E. Meydani, et al., “The “Black Box” of Social Commerce Platforms - A Closer Look at Users’ Activities”, Proceedings of the 17th International Conference on Wirtschaftsinformatik, 2022.

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• [1]
  

  2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2960371

  E. Meydani, C. Düsing, and M. Trier, “Towards a Trust-aware Item Recommendation System on a Graph Autoencoder with Attention Mechanism”, Proceedings of the 16th International Conference on Wirtschaftsinformatik, 2021.

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