The formulation of trace quotient is shared by many computer vision problems; however, it was conventionally approximated by an essentially different formulation of quotient trace,...
Multi-instance learning deals with problems that treat bags of instances as training examples. In single-instance learning problems, dimensionality reduction is an essential step ...
The creation of language resources for less-resourced languages like the historical ones benefits from the exploitation of language-independent tools and methods developed over th...
The resource constraint project scheduling problem (RCPSP) is an NP-hard benchmark problem in scheduling which takes into account the limitation of resources’ availabilities in ...
Abstract: The Principal Component Analysis (PCA) is a data dimensionality reduction technique well-suited for processing data from sensor networks. It can be applied to tasks like ...