mércores, maio 20, 2020

mércores, 20 maio, 2020 -
10:00 - 11:00

Today we live in a context in which devices are increasingly interconnected and sensorized and are almost ubiquitous. Deep learning has become in recent years a popular way to extract knowledge from the huge amount of data that these devices can collect.

Nevertheless, state-of-the-art learning methods have several drawbacks when facing real distributed problems, in which the available information is usually partial, biased, and changing over time. Moreover, if there is something that characterizes this society of devices is its high heterogeneity and dynamism, both in terms of users and the hardware itself.