most citedA network-based transfer learning approach to improve sales forecasting of new products

7 citations · 7 across the 2 of their papers we have counts for

collaborators

5 papers

cs.LG2020

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…

cs.LG20207 cited

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…

cs.LG2020

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…

cs.LG2020

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…

cs.LG2020

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…