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Research Seminar - Machine Learning for Predicting in a Big Data World

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Speaker: Prof. Gianluca Bontempi (Université Libre de Bruxelles)
Event date: Thursday, 28 February 2019 03:00 pm - 04:00 pm
Place: Room E004, JFK Building
29 Avenue J.F. Kennedy
L-1855 Kirchberg

The increasing availability of massive amounts of data and the need of performing accurate forecasting of future behavior in several scientific and applied domains demands the definition of robust and efficient techniques able to infer from observations the stochastic dependency between past and future. The forecasting domain has been influenced, from the 1960s on, by linear statistical methods such as ARIMA models. More recently, machine learning models have attracted attention and have established themselves as serious contenders to classical statistical models in the forecasting community.

This talk will present an overview of machine learning techniques in time series forecasting and will focus on machine learning strategies to address three important tasks: univariate one-step-ahead prediction, univariate multi-step-ahead prediction and multivariate multi-step-ahead forecasting. Also, it will present DFML, a machine learning version of the Dynamic Factor Model (DFM), a successful forecasting methodology well-known in econometrics. The DFML strategy is based on an out-of-sample selection of the nonlinear forecaster, the number of latent components and the multi- step-ahead strategy. We will show that DFML can consistently outperform state-of-the-art methods in a number of synthetic and real forecasting tasks.

Gianluca Bontempi is Full Professor in the Computer Science Department at the Université Libre de Bruxelles (ULB), Brussels, Belgium, founder and co-head of the ULB Machine Learning Group. His main research interests are big data mining, machine learning, bioinformatics, causal inference, predictive modelling and their application to complex tasks in engineering (forecasting, fraud detection) and life science. He was Marie Curie fellow researcher, he was awarded in two international data analysis competitions and he took part in many research projects in collaboration with universities and private companies all over Europe. From 2013-17 he was Director of the ULB/VUB Interuniversity Institute of Bioinformatics in Brussels. He is author of more than 200 scientific publications and an IEEE Senior Member. He is also co-author of several open-source software packages for bioinformatics, data mining and prediction.