- Research Grants
graduation at Ciência da Computação from Universidade Estadual do Centro-Oeste (2013) and master's at Computer Science from Universidade de São Paulo (2016). Has experience in Computer Science, acting on the following subjects: câncer de próstata, rede neural artificial com função de base radial, rede neural artificial multilayer perceptron, learning vector quantization and ainet e k-means. (Source: Lattes Curriculum)
In the recent years, machine learning techniques have been extensively used for bioinformatics, due to their capacity in solving hard problems by learning a function from a set of known examples which is able to make predictions for new and unseen data. Motivated by such results we will tackle in this project three different bioinformatics problems using machine learning techniques: (i)...
One of the main subjects in machine learning is data clustering, which aims at finding clusters that describe a set of objects in such a way that the intra-cluster similarity and inter-cluster dissimilarity are both maximized. In general, such techniques are based on measures that take into account all the available features of a dataset. However, in several real-world situations the cl...
Cluster analysis is a fundamental problem of unsupervised machine learning where the objective is to determine categories that describe a set of objects according to their similarities and inter-relationships. In the traditional formulation of the problem one seeks partitions or hierarchies of partitions containing groups whose objects are in some way similar among themselves and dissim...
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
|Data from Web of Science|
(References retrieved automatically from State of São Paulo Research Institutions)
PADILHA, Victor Alexandre. Avaliação sistemática de técnicas de bi-agrupamento de dados. 2016. Dissertação (Mestrado) - Instituto de Ciências Matemáticas e de Computação. Universidade de São Paulo (USP). São Carlos.