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Seminars


22 May

Advanced Database Techniques for Processing Scientific Multi-Dimensional Data and Stochastic Gradient Descent on Highly-Parallel Architectures: Multi-core CPU or GPU? Synchronous or Asynchronous?

Presentation 1: Advanced Database Techniques for Processing Scientific Multi-Dimensional Data Abstract Scientific applications are generating an ever-increasing volume of multi-dimensional data that require fast analytics to extract meaningful results. The database community has developed distribu...
02 February

Large Volume Data Management

Introduction to MongoDB, a NoSQL database - or as authors prefer: dynamic schema. Brief explanation of the theoretical basis, with a complement on the practical part of how to build a scalable infrastructure of easy administration and monitoring with redundancy, high availability and security....
11 August

Search in Algorithms and Applications in Data Mining in the context of CEFET / RJ

Data Mining (MD) is the process of analyzing object collections to detect systematic relationships between the properties of these objects to generate knowledge that is not easily detected. The MD process includes four general steps: data selection, data preprocessing, MD methods and algorithms, and...
02 June

$Upsilon$-DB: Managing Scientific Hypotheses as Uncertain and Probabilistic Data

In view of the paradigm shift that makes science ever more data-driven, we consider deterministic scientific hypotheses as uncertain data. This vision comprises a probabilistic database (p-DB) design methodology for the systematic construction and management of U-relational hypothesis DBs, vi...
19 May

MongoDB, an overview of the tool

Introduction to MongoDB, a NoSQL database - or as authors prefer: dynamic schema. Brief explanation of the theoretical basis, with a complement on the practical part of how to build a scalable infrastructure of easy administration and monitoring with redundancy, high availability and security.