Ricardo José Gabrielli Barreto Campello

• Abstract

  This document formalizes a research proposal for funding from the Research Foundation of the State of São Paulo (FAPESP). The main objective is to support the research group of the applicant for a period of two years. The group is mainly constituted by the researcher and his students at ICMC / USP, but the project will also involve international collaborations with the University of Alber…

  Methods and algorithms in unsupervised and semi-supervised machine learning, AP.R
• Control of a bioprocess using orthonormal basis function fuzzy models., AR.EXT

• Abstract

  Outlier detection plays an important role in the pattern discovery from data that can be considered exceptional in some sense. Detecting such patterns is relevant in general because in many data mining applications, such patterns represent extraordinary behaviors that is worth further analysis. An important distinction is that between the supervised and unsupervised techniques. In this pr…

  Evaluation, model selection and unsupervised outlier detection in data spaces and subspaces, BP.DR

• Abstract

  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 dissimil…

  Systematic Evaluation of Bi-clustering Techniques, BP.MS

• Abstract

  There are many situations in machine learning in which it is easy to obtain vast amounts of unlabeled data, but it is costly to obtain labels for these data. This leads to typical situations in which only a small subset of labeled data is available, which is not representative enough for learning a model in a supervised way. In such situations, techniques that are able to learn from both …

  Active, semi-supervised learning for classification and clustering, BP.MS

(Only some records are available in English at this moment)

• Abstract

  This document describes a research proposal for a 1 year sabbatical period under the supervision of Prof. Joerg Sander from the Databases (DB) Group of the Department of Computing Science of the University of Alberta (U of A), in Edmonton, Canada. The preliminary conception of this proposal was envisaged during a 1 week visit of Ricardo J. G. B. Campello (candidate) to the DB group of the…

  Study and development of validation methods for density- and graph-based clustering techniques, BE.PQ