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Research

I write about various topics in computer science and economics:

Machine Learning  Artificial Intelligence    Federated Machine Learning     Meta-Learning     AI Explainability    Distributed Systems  

2020

Karb, T.; Kühl, N.; Hirt, R.; Glivici-Cotruță, V.

A network-based transfer learning approach to improve sales forecasting of new products.

European Conference on Information Systems (ECIS) - Marrakech, Marocco, June 15 - 17, 2020

2017

Hirt, R.; Kühl, N.

Abbildung kognitiver Fähigkeiten mit Metamodellen.

INFORMATIK 2017, 47. Jahrestagung der Gesellschaft für Informatik, Chemnitz, Deutschland, 25. - 29. September 2017. Hrsg.: Maximilian Eib, 2301–2307, Gesellschaft für Informatik e.V. (GI). doi:10.18420/in2017_231

2017

Hirt, R.; Kühl, N.; Satzger, G.

An End-to-End Process Model for Supervised Machine Learning Classification : From Problem to Deployment in Information Systems.

Designing the Digital Transformation, DESRIST 2017 Research in Progress Proceedings of the 12th International Conference on Design Science Research in Information Systems and Technology, Karlsruhe, Germany, 30th May - 1st June 2017. Ed.: A. Mädche, 55–63, Karlsruher Institut für Technologie (KIT)

2018

Hirt, R.; Kühl, N.

Cognition in the Era of Smart Service Systems: Inter-organizational Analytics through Meta and Transfer Learning.

39th International Conference on Information Systems, ICIS 2018; San Francisco Marriott MarquisSan Francisco; United States; 13 December 2018 through 16 December 2018, AIS eLibrary (AISeL)

2019

Hirt, R.; Kühl, N.; Satzger, G.

Cognitive computing for customer profiling: meta classification for gender prediction.

Electronic markets, 29 (1), 93–106. doi:10.1007/s12525-019-00336-z

2020

Walk, J.; Hirt, R.; Kühl, N.; Hersløv, E. R.

Half-empty or half-full? A Hybrid Approach to Predict Recycling Behavior of Consumers to Increase Reverse Vending Machine Uptime.

2020. Exploring Service Science : 10th International Conference on Exploring Service Science, IESS 2020, Porto, Portugal, February 05-07, 2020. Proceedings. Ed.: H. Nóvoa, Springer International Publishing. doi:10.1007/978-3-030-38724-2_8

2020

Kühl, N.; Hirt, R.; Baier, L.; Schmitz, B.; Satzger, G.

How to Conduct Rigorous Supervised Machine Learning in Information Systems Research: The Supervised Machine Learning Reportcard.

Communications of the Association for Information Systems

2017

Hirt, R.

How to Cope With Incomplete Prediction Input? A Categorization of Techniques For Realizing Robust Analytics for Smart Service Systems.

3rd Karlsruhe Service Summit Research Workshop, Karlsruhe, Germany, 21st - 22nd September 2017

2020

Hirt, R.; Kühl, N.; Peker, Y.; Satzger, G.

How to Learn from Others: Transfer Machine Learning with Additive Regression Models to Improve Sales Forecasting.

22nd IEEE Conference on Business Informatics, CBI 2020, Antwerp, Belgium, 22 - 24 June 2020, 20–29, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/CBI49978.2020.00010

2019

Hirt, R.; Kühl, N.

How to Learn from Others? A Research Agenda on Transfer Machine Learning for Sales Forecasting.

February 19. MIT-IBM Watson AI Lab (2019), Cambridge, MA, USA, March 19, 2019

2019

Kühl, N.; Goutier, M.; Hirt, R.; Satzger, G.

Machine Learning in Artificial Intelligence: Towards a Common Understanding.

Hawaii International Conference on System Sciences (HICSS-52), Grand Wailea, Maui, Hawaii, Januar 8-11, 2019

2021

Hirt, R.; Srivastava, A.; Berg, C.; Kühl, N.

Sequential Transfer Machine Learning in Networks: Measuring the Impact of Data and Neural Net Similarity on Transferability.

Hawaii International Conference on Systems Sciences (HICSS-54), January 5-8, 2021

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