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Today, in many areas, we collect huge volumes of data to analyse. To use this data in classification methods it is necessary to aggregate them keeping as much information as possible about the data. Histograms are a useful way of representing large sets of data keeping information about the structure and variability. The analysis and classification methods for symbolic data are in general more complex than for standard data. In this talk we will present a new method for discriminant analysis for histogram data and describe its connection with fractional quadratic optimization problems. About the speaker: Paula Amaral is an Assistant Professor of the Department of Mathematics at FCT NOVA and a member of the Center for Mathematics and Applications (CMA) at Universidade Nova de Lisboa. She has a degree and Master in Statistics and Operational Research from the University of Lisbon and a PhD in Mathematics from the New University of Lisbon. Her research area is in Optimization, Modeling and Optimization for Machine Learning. She has supervised several internships in industrial and consulting companies such as Telepac, Águas de Portugal, CTT, GALP and supervised masters students from national (FCT UNL) and international schools (Sapienza, Rome). She is a member of the Executive Committee of the CMA and a member of the Board of Europt (European Group for Continuous Optimization).
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