Kernel methods are effective approaches to the modeling of structured objects in learning algorithms. Their major drawback is the typically high computational complexity of kernel ...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...
We review current methods for evaluating models in the cognitive sciences, including theoretically-based approaches, such as Bayes Factors and MDL measures, simulation approaches,...
Richard M. Shiffrin, Michael D. Lee, Woojae Kim, E...
Extensive software-based simulation continues to be the mainstream methodology for functional verification of designs. To optimize the use of limited simulation resources, coverag...
Onur Guzey, Li-C. Wang, Jeremy R. Levitt, Harry Fo...
— Accurate query performance prediction (QPP) is central to effective resource management, query optimization and query scheduling. Analytical cost models, used in current genera...
For the purpose of exploring and modelling the relationships between a dataset and several datasets, multiblock Partial Least Squares is a widely-used regression technique. It is d...