Graph models for machine learning: K-associated graphs and Attribute-based Decision Graphs
Prof. João Bertini (FT/Limeira) [slides] [video]
Abstract: Graph-based methods consist of a powerful form of data representation and abstraction. Among other features, they allow uncovering topological relationships, visualizing structures, representing groups of data with different formats, and providing alternative measures to characterize the data. However, the majority of traditional graph-based methods, in general, presents a high computational complexity order, which limits the scope of application of these methods. In this context, alternative approaches based on graphs, such as K-associated graphs and Attribute-based Decision Graphs, present low computational complexity and, at the same time, have the advantages of graph-based learning. This talk will address general aspects of both models, as well as some of their applications to machine learning tasks, such as supervised and semi-supervised classification, learning from data streams, imputation of missing attribute values and enhancement of the data quality for classification tasks.
When: Thursday August 16th @11am.
Where: IC Amphitheater.
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Reverse engineering of video content for forensic analysis: model-based and data-driven approaches.
Prof. Paolo Bestagini (Politecnico di Milano, Italy) [slides] [video]
Abstract: The recent development of multimedia devices and editing tools, together with the proliferation of video sharing websites, has made the acquisition, alteration, and diffusion of video content relatively easy tasks. As a consequence, it is possible to find more and more video sequences available on the Internet, but each of them has been potentially tampered with by anyone. It is then clear that the development of tools that enable the recovery of past history of video sequences in order to prove their origin and authenticity is more than an urgent necessity. In this talk, we discuss some of the video forensic techniques that have proposed in the last few years. Specifically, we will focus on blind forensic methods exploiting either model-based or data-driven solutions.
Mini vita: Paolo Bestagini received the B.Sc. and M.Sc. in Telecommunications Engineering at the Politecnico di Milano in 2008 and 2010, respectively. Since 2011, he joined the Image and Sound Processing Group (ISPG) at the Politecnico di Milano, and he received his Ph.D. in Information Technology in 2014. Since 2016 he is Assistant Professor at the Image and Sound Processing Group, Politecnico di Milano. His research interests focus on multimedia forensics and acoustic signal processing for microphone arrays. He is an elected member of the IEEE Information Forensics and Security Technical Committee, and a co-organizer of the IEEE Signal Processing Cup 2018.
When: Friday August 17th @2pm.
Where: IC Amphitheater
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Saiba como inteligência artificial é usada para criar fake news
RECOD — Reasoning for Complex Data 