arXiv Machine Learning By Julio Gonz\'alez-D\'iaz, Beatriz Pateiro-L\'opez, Iria Rodr\'iguez-Acevedo

A new classification method based on Minimum Spanning Trees

Read the original on arXiv Machine Learning →

arXiv:2606. 21639v2 Announce Type: replace Abstract: 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 inconsistent in defining those clusters.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv Machine Learning
Jun 30

Optimizing Nursing Care Taxi Dispatch Leveraging Integer Linear Programming Solvers and Machine Learning

arXiv:2606. 29725v1 Announce Type: new Abstract: In this paper, we formulate a new vehicle dispatch optimization problem, called Nursing Care Taxi Dispatch, as a variant of the Vehicle Routing Problem, considering constraints related to wheelchair use, user compatibility, pick-up and drop-off times, and vehicle limitations.

By Riku Nakao, Akihito Hiromori, Hamada Rizk, Hirozumi Yamaguchi
arXiv Machine Learning
Jul 21

A Survey of Features Used for Representing Black-box Single-objective Continuous Optimization

arXiv:2406. 06629v2 Announce Type: replace Abstract: This survey examines key advancements in designing features to represent optimization problem instances, algorithm instances, and their interactions within the context of single-objective continuous black-box optimization.

By Gjorgjina Cenikj, Ana Nikolikj, Ga\v{s}per Petelin, Niki van Stein, Carola Doerr, Tome Eftimov
arXiv AI
Jun 2

Unsupervised Cognition

arXiv:2409. 18624v4 Announce Type: replace Abstract: Unsupervised learning methods have a soft inspiration in cognition models.

By Alfredo Ibias, Hector Antona, Guillem Ramirez-Miranda, Enric Guinovart, Eduard Alarcon