Cutting plane methods play a significant role in modern solvers for tackling mixed-integer
programming (MIP) problems. Proper selection of cuts would remove infeasible solutions in …

Morphological image operators are a class of non-linear image mappings studied in
Mathematical Morphology. Many significant theoretical results regarding the characterization …

An important problem in bioinformatics is the inference of gene regulatory networks (GRNs)
from expression profiles. In general, the main limitations faced by GRN inference methods …

A classical approach to designing binary image operators is mathematical morphology
(MM). We propose the Discrete Morphological Neural Networks (DMNN) for binary image …

We introduce a fast Branch-and-Bound algorithm for optimal feature selection based on a U-
curve assumption for the cost function. The U-curve assumption, which is based on the …

In Machine Learning, feature selection is an important step in classifier design. It consists of
finding a subset of features that is optimum for a given cost function. One possibility to solve …

The U-curve optimization problem is characterized by a decomposable in U-shaped curves
cost function over the chains of a Boolean lattice. This problem can be applied to model the …

In this paper, we introduce featsel, a framework for benchmarking of feature selection
algorithms and cost functions. This framework allows the user to deal with the search space …

The machine learning of lattice operators has three possible bottlenecks. From a statistical
standpoint, it is necessary to design a constrained class of operators based on prior …

Cross-validation techniques for risk estimation and model selection are widely used in
statistics and machine learning. However, the understanding of the theoretical properties of …