Gabriele Ciravegna (University of Florence) Oct 28, 2020 – 11:00 – 11:45 AM Conference Meeting Description One of the key limitations of modern deep learning approaches lies in the amount of data required to train them. Humans, by contrast, can learn to recognize novel categories from just a few examples. Instrumental to this rapid learning […]

Anna Visibelli (University of Siena) Oct 21, 2020 – 11:00 – 11:45 AM Conference Meeting Description Vast majority of human genetic disorders are associated with mutations that affect protein-protein interactions by altering wild type binding affinity. Therefore, it is extremely important to assess the effect of mutations on protein-protein binding free energy to assist the […]

Giorgio Ciano (University of Florence) Oct 7, 2020 – 11:00 – 11:45 AM Conference Meeting Description Chest X-ray radiography is one of the earliest medical imaging technologies and remains one of the most widely-used for diagnosis, screening, and treatment follow up of diseases related to lungs and heart. The literature in this field of research […]

Lapo Faggi (University of Florence) Sep 30, 2020 – 11:00 AM Conference Meeting Description In this seminar, some recent imitation learning algorithms will be presented. Imitation learning, also known as learning from demonstrations, is a powerful and practical alternative to reinforcement learning for learning sequential decision-making policies without the need of defining any (hand-crafted) reward […]

Marco Ernandes Sep 23, 2020 – 11:45 – 12:30 AM Conference Meeting Description The text-mining field is currently in the eye of a technological storm: dozens of novel (and effective!) algorithms and architectures have been recently released, mainly by global AI players, such as Google, OpenAI, Microsoft. From a methodological point of view we observe […]

Niccolò Pancino (University of Florence) Sep 23, 2020 – 11:00 – 11:45 AM Conference Meeting Description Spectral clustering (SC) is a popular clustering technique to find strongly connected communities on a graph. It can be used in Graph Neural Networks to implement pooling operations that aggregate nodes belonging to the same cluster. However, SC is […]

Enrico Meloni (University of Florence) Sep 16, 2020 – 11:00 AM Conference Meeting Description Recently, researchers in Machine Learning algorithms, Computer Vision scientists, engineers, and others, showed a growing interest in 3D simulators as a mean to artificially create experimental settings that are remarkably close to those in the real world. However, most of the […]

Pietro Bongini (University of Florence) Sep 2, 2020 – 11:00 AM Conference Meeting Description The generation of graph–structured data is an emerging problem in the field of deep learning. Various solutions have been proposed in the last few years, yet the exploration of this branch is still in an early phase. Graph data being ubiquitous […]

Federica Baccini (University of Florence) Jul 22, 2020 – 11:00 AM Conference Meeting Description Similarity network fusion is a tool that aggregates the information coming from a multiplex network into a unique layer through a cross diffusion process. However, the process itself does not allow to infer which layer has the major impact in the […]

Gabriele Ciravegna (University of Florence) Jul 15, 2020 – 11:00 AM Conference Meeting Description Adversarial attacks on machine learning-based classifiers, along with defence mechanisms, have been widely studied in the context of single-label classification problems. In this paper, we shift the attention to multi-label classification, where the availability of domain knowledge on the relationships among […]