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The field of machine learning (ML) is concerned with the question of how to construct algorithms that automatically improve with experience. In recent years many successful ML applications have been developed, such as da...

This book is a material aimed at training new graduates and updating practising professionals within the framework of early childhood care (0-6 years). It also opens up training to new professions such as health engineer...

Several interdisciplinary studies highlight imperfect information as a possible explanation of skill mismatches, which in turn has implications for unemployment and informality rates. Despite information failures and the...

We are pleased to present to the entire academic community and the general public the following work, which contains recent research results of a group of teachers from the Faculty of Educational Sciences in areas such a...

Numerical Taxonomy aims to group in clusters, using so-called structure analysis of operational taxonomic units (OTUs or taxons or taxa) through numerical methods. Clusters that consitute families was the purpose of this...

Clustering techniques can be used as a basis for classification systems in which clusters can be classified into two categories: positive and negative. Given a new instance enew, the classification algorithm is applied t...

As one of the most successful applications of image analysis and understanding, face recognition has recently received significant attention, especially during the past several years. At least two reasons account for thi...

This monograph is a self-contained, coherent presentation of the background and progress of the stability of time-delay systems. Focusing on techniques, tools, and advances in numerical methods and op

We describe latent Dirichlet allocation (LDA), a generative probabilistic model for collections of discrete data such as text corpora. LDA is a three-level hierarchical Bayesian model, in which each item of a collection ...