14 citations · 21 across the 6 of their papers we have counts for
6 papers
Enabling Inter-organizational Analytics in Business Networks Through Meta Machine Learning
Robin Hirt, Niklas Kühl, Dominik Martin +1
Successful analytics solutions that provide valuable insights often hinge on the connection of various data sources. While it is often feasible to generate larger data pools within…
How to Learn from Others: Transfer Machine Learning with Additive Regression Models to Improve Sales Forecasting
Robin Hirt, Niklas Kühl, Yusuf Peker +1
In a variety of business situations, the introduction or improvement of machine learning approaches is impaired as these cannot draw on existing analytical models. However, in many…
A network-based transfer learning approach to improve sales forecasting of new products
Tristan Karb, Niklas Kühl, Robin Hirt +1
Data-driven methods -- such as machine learning and time series forecasting -- are widely used for sales forecasting in the food retail domain. However, for newly introduced produc…
Half-empty or half-full? A Hybrid Approach to Predict Recycling Behavior of Consumers to Increase Reverse Vending Machine Uptime
Jannis Walk, Robin Hirt, Niklas Kühl +1
Reverse Vending Machines (RVMs) are a proven instrument for facilitating closed-loop plastic packaging recycling. A good customer experience at the RVM is crucial for a further pro…
Sequential Transfer Machine Learning in Networks: Measuring the Impact of Data and Neural Net Similarity on Transferability
Robin Hirt, Akash Srivastava, Carlos Berg +1
In networks of independent entities that face similar predictive tasks, transfer machine learning enables to re-use and improve neural nets using distributed data sets without the…
Machine Learning in Artificial Intelligence: Towards a Common Understanding
Niklas Kühl, Marc Goutier, Robin Hirt +1
The application of "machine learning" and "artificial intelligence" has become popular within the last decade. Both terms are frequently used in science and media, sometimes interc…