1 citations · 1 across the 4 of their papers we have counts for
4 papers
A new classification method based on Minimum Spanning Trees
Julio González-Díaz, Beatriz Pateiro-López, Iria Rodríguez-Acevedo
Minimum Spanning Trees have been used in unsupervised learning, particularly in clustering tasks, due to their ability to recognize clusters by removing edges that are considered i…
Learning in Spatial Branching: Limitations of Strong Branching Imitation
Brais González-Rodríguez, Ignacio Gómez-Casares, Bissan Ghaddar +2
Over the last few years, there has been a surge in the use of learning techniques to improve the performance of optimization algorithms. In particular, the learning of branching ru…
Statistical analysis of measures of non-convexity
Alejandro Cholaquidis, Ricardo Fraiman, Leonardo Moreno +1
Several measures of non-convexity (departures from convexity) have been introduced in the literature, both for sets and functions. Some of them are of geometric nature, while other…
Learning for Spatial Branching: An Algorithm Selection Approach
Bissan Ghaddar, Ignacio Gómez-Casares, Julio González-Díaz +3
The use of machine learning techniques to improve the performance of branch-and-bound optimization algorithms is a very active area in the context of mixed integer linear problems,…