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Enabling Inter-organizational Analytics in Business Networks Through Meta Machine Learning
While it is often feasible to generate larger data pools within organizations, the application of analytics within (inter-organizational) business networks is still severely constrained.
How to Learn from Others: Transfer Machine Learning with Additive Regression Models to Improve Sales Forecasting
For the particular purpose of sales forecasting for similar entities, we propose a transfer machine learning approach based on additive regression models that lets new entities benefit from models of existing entities.
A network-based transfer learning approach to improve sales forecasting of new products
A network-based Transfer Learning approach for deep neural networks is designed to investigate the efficiency of Transfer Learning in the domain of food sales forecasting.
Half-empty or half-full? A Hybrid Approach to Predict Recycling Behavior of Consumers to Increase Reverse Vending Machine Uptime
Bin full events are the major reason for Reverse Vending Machine (RVM) downtime at the world leader in the RVM market.
Sequential Transfer Machine Learning in Networks: Measuring the Impact of Data and Neural Net Similarity on Transferability
As the number of data sets in business networks grows and not every neural net transfer is successful, indicators are needed for its impact on the target performance-its transferability.
Machine Learning in Artificial Intelligence: Towards a Common Understanding
The application of "machine learning" and "artificial intelligence" has become popular within the last decade.
