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Robin Hirt
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2020 – today
- 2023
- [i6]Robin Hirt, Niklas Kühl, Dominik Martin, Gerhard Satzger:
Enabling Inter-organizational Analytics in Business Networks Through Meta Machine Learning. CoRR abs/2303.15834 (2023) - 2021
- [j2]Niklas Kühl, Robin Hirt, Lucas Baier, Björn Schmitz, Gerhard Satzger:
How to Conduct Rigorous Supervised Machine Learning in Information Systems Research: The Supervised Machine Learning Report Card. Commun. Assoc. Inf. Syst. 48: 46 (2021) - [c10]Robin Hirt, Akash Srivastava, Carlos Berg, Niklas Kühl:
Sequential Transfer Machine Learning in Networks: Measuring the Impact of Data and Neural Net Similarity on Transferability. HICSS 2021: 1-10 - 2020
- [c9]Tristan Karb, Niklas Kühl, Robin Hirt, Varvara Glivici-Cotruta:
A Network-based Transfer Learning Approach to Improve Sales Forecasting of New Products. ECIS 2020 - [c8]Jannis Walk, Robin Hirt, Niklas Kühl, Erik R. Hersløv:
Half-Empty or Half-Full? A Hybrid Approach to Predict Recycling Behavior of Consumers to Increase Reverse Vending Machine Uptime. IESS 2020: 107-120 - [c7]Florin Tim Peters
, Robin Hirt
A Transfer Machine Learning Matching Algorithm for Source and Target (TL-MAST). LOD (2) 2020: 541-558 - [c6]Robin Hirt, Niklas Kühl, Yusuf Peker, Gerhard Satzger
How to Learn from Others: Transfer Machine Learning with Additive Regression Models to Improve Sales Forecasting. CBI (1) 2020: 20-29 - [i5]Robin Hirt, Akash Srivastava, Carlos Berg, Niklas Kühl:
Sequential Transfer Machine Learning in Networks: Measuring the Impact of Data and Neural Net Similarity on Transferability. CoRR abs/2003.13070 (2020) - [i4]Jannis Walk, Robin Hirt, Niklas Kühl, Erik R. Hersløv:
Half-empty or half-full? A Hybrid Approach to Predict Recycling Behavior of Consumers to Increase Reverse Vending Machine Uptime. CoRR abs/2003.13304 (2020) - [i3]Niklas Kühl, Marc Goutier, Robin Hirt, Gerhard Satzger:
Machine Learning in Artificial Intelligence: Towards a Common Understanding. CoRR abs/2004.04686 (2020) - [i2]Tristan Karb, Niklas Kühl, Robin Hirt, Varvara Glivici-Cotruta:
A network-based transfer learning approach to improve sales forecasting of new products. CoRR abs/2005.06978 (2020) - [i1]Robin Hirt, Niklas Kühl, Yusuf Peker, Gerhard Satzger:
How to Learn from Others: Transfer Machine Learning with Additive Regression Models to Improve Sales Forecasting. CoRR abs/2005.10698 (2020)
2010 – 2019
- 2019
- [b1]Robin Hirt:
Supervised machine learning in service systems: deriving insights from distributed data. Karlsruhe Institute of Technology, Germany, 2019, pp. 1-183 - [j1]Robin Hirt
Cognitive computing for customer profiling: meta classification for gender prediction. Electron. Mark. 29(1): 93-106 (2019) - [c5]Niklas Kühl, Marc Goutier, Robin Hirt, Gerhard Satzger:
Machine Learning in Artificial Intelligence: Towards a Common Understanding. HICSS 2019: 1-10 - [c4]Dominik Martin, Robin Hirt, Niklas Kühl:
Service Systems, Smart Service Systems and Cyber- Physical Systems - What's the difference? Towards a Unified Terminology. Wirtschaftsinformatik 2019: 17-31 - 2018
- [c3]Robin Hirt, Niklas Kühl, Björn Schmitz, Gerhard Satzger:
Service-Oriented Cognitive Analytics for Smart Service Systems: A Research Agenda. HICSS 2018: 1-8 - [c2]Robin Hirt, Niklas Kühl:
Cognition in the Era of Smart Service Systems: Inter-organizational Analytics through Meta and Transfer Learning. ICIS 2018 - 2017
- [c1]Robin Hirt, Niklas Kühl:
Abbildung kognitiver Fähigkeiten mit Metamodellen. GI-Jahrestagung 2017: 2301-2307
Coauthor Index
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