This book contains details of the properties that satisfy certain function spaces and vector-valued distributions defined in the n-dimensional torus. In particular, the text deals with an introductory ...

Abstract In this paper, we introduce the concept of a weak q-distance and for this distance we derive a set-valued version of Ekeland's variational principle in the setting of uniform spaces. By using ...

If the space of all real-valued functions of bounded variation on a real closed interval is endowed with the topology of simple convergence, then every bounded subset which is bounded for the values ...

Support Vector Machines (SVMs) represent a robust and versatile class of machine learning algorithms that have significantly shaped the fields of pattern recognition, classification, and regression.

Support Vector Machines (SVMs) have become a cornerstone of machine learning, widely adopted for their robustness in classification and regression tasks across diverse fields ranging from remote ...