Cost Estimation for Factorized Machine Learning in Data Integration Scenarios

The workflow of a data science practitioner includes gathering information from different sources and applying machine learning (ML) models. Such dispersed information can be combined through a process known as Data Integration (DI), which defines relations between entities and attributes. When all information is combined in one source suited...

Dimension reduction techniques for multi-dimensional numerical integrations based on Fourier-cosine series expansion

A wide range of practical problems involve computing multi-dimensional integrations. However, in most cases, it is hard to find analytical solutions to these multi-dimensional integrations. Their numerical solutions always suffer from the `curse of dimension', which means the computational complexity grows exponentially with respect to the...

Machine learning in Maritime Technology: Energy storage size reduction using load forecasting for pipelaying vessels

During dynamic positioning operations, vessels typically run with an extra generator (spinning reserve) for redundancy purposes such that no single fault will cause the vessel to lose its position or heading. As a result, all other engines on the grid share the load equally to ensure that if a failure were to occur, the remaining healthy...