We introduce unprecedented tools to infer approximate evolution features of the COVID19
outbreak when these features are altered by containment measures. In this framework we …

We provide an estimation procedure of the two-parameter Gamma distribution based on the
Algorithmic Inference approach. As a key feature of this approach, we compute the joint …

With the aim of getting understandable symbolic rules to explain a given phenomenon, we
split the task of learning these rules from sensory data in two phases: a multilayer perceptron …

While there is currently a significant amount of work being done to promote competency-
based education (CBE), many efforts are focused on the design, development …

We revise the notion of confidence with which we estimate the parameters of a given
distribution law in terms of their compatibility with the sample we have observed. This is a …

We discuss a procedure which extracts statistical and entropic information from data in order
to discover Boolean rules underlying them. We work within a granular computing framework …

This article describes the deliberate making of a knowledge community to advance
specialization in divided labor and structuring a successful enterprise. A knowledge network …

We devise a feature selection method in terms of a follow-out utility of a special classification
procedure. In turn, we root the latter on binary features which we extract from the input …

We formulate a new family of bootstrap algorithms suitable for learning non-Boolean
functions from data. Within the Algorithmic Inference framework, the key idea is to consider a …

We introduce a regression method that fully exploits both global and local information about
a set of points in search of a suitable function explaining their mutual relationships. The …