Link para a participação no Seminário via Zoom:
Orador Convidado: Milan Stehlík (Linz Institute of Technology, Johannes Kepler University in Linz, Linz, Austria
Institute of Statistics, Universidad de Valparaíso, Valparaíso, Chile)
Resumo: During the talk we speak on learning mechanisms of data transformation, aggregation (see Stehlík 2016), and fusion. We will discuss the data science aspects of transformations, with their mathematical and statistical properties (see Stehlík et al 2017). We will introduce SPOCU transfer function for neural networks (see Kiselak et al 2020) and provide some of its unique properties for processing of complex data, also with its behavior. General statistical learning will be also discussed.
Resumo (pdf):
Em Anexo.
