Renato Rodrigues Oliveira da Silva

Federal Institute of São Paulo | IFSP · Programa Tecnologia em Análise e Desenvolvimento de Sistemas

Graph visualization has been successfully applied in a wide range of problems and applications. Although different approaches are available to create visual representations, most of them suffer from clutter when faced with many nodes and/or edges. Among the techniques that address this problem, edge bundling has attained relative success in improvi...

Similarity-based exploration of multi-dimensional data sets is a difficult task, in which most techniques do not perform well with large data sets, particularly in handling clutter that invariably happens as data sets grow larger. In this paper, we introduce the Visual SuperTree (VST), a method to build a multi-scale similarity tree that can deal w...

Multidimensional projections are an increasingly popular technique for visualizing large datasets containing observations having tens or even hundreds of dimensions. Compared to other techniques such as parallel coordinates, tables, and scatterplot matrices, they support tasks such as finding groups of related observations and outliers in simpler,...

Multidimensional projections (MPs) are key tools for the analysis of multidimensional data. MPs reduce data dimensionality while keeping the original distance structure in the low-dimensional output space, typically shown by a 2D scatterplot. While MP techniques grow more precise and scalable, they still do not show how the original dimensions (att...

Feature selection is an important step in designing image classification systems. While many automatic feature selection methods exist, most of them are opaque to their users. We consider that users should be able to gain insight into how observations behave in the feature space, since this may allow the design of better features and the incorporat...

Multilabel classification is an important problem in bioinformatics and Machine Learning. In a conventional classification problem, examples belong to just one among many classes. When an example can simultaneously belong to more than one class, the classification problem is named multilabel classification problem. Protein function classification i...