Many facial image analysis methods rely on learningbased techniques such as Adaboost or SVMs to project classifiers based on the selection of local image filters (e.g., Haar and...
This paper investigates a class of learning problems called learning satisfiability (LSAT) problems, where the goal is to learn a set in the input (feature) space that satisfies...
Frederic Thouin, Mark Coates, Brian Eriksson, Robe...
We show how a random mutation hill climber that does multilevel selection utilizes transposition to escape local optima on the discrete Hierarchical-If-And-Only-If (HIFF) problem....
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
A key step in the optimization of declarative queries over XML data is estimating the selectivity of path expressions, i.e., the number of elements reached by a specific navigatio...
Natasha Drukh, Neoklis Polyzotis, Minos N. Garofal...