Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...
Algorithms for feature selection fall into two broad categories: wrappers that use the learning algorithm itself to evaluate the usefulness of features and filters that evaluate f...
Multiple Sequence Alignment (MSA) is one of the most fundamental problems in computational molecular biology. The running time of the best known scheme for finding an optimal ali...
Efficient production testing is frequently hampered because current digital circuits require test sets which are too large. These test sets can be reduced significantly by means...
M. J. Geuzebroek, J. Th. van der Linden, A. J. van...
In Computer Graphics, Collision Detection is considered a key problem with important applications in related areas. Several solutions have been proposed, but independently of the ...
Lidia M. Ortega, Francisco R. Feito, Clara I. Grim...