[Sep 30th 2020] LabMeeting: Imitation Learning – predicting goal-directed scanpaths

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 […]

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[Sep 23rd 2020] LabMeeting: Evaluating the impact of semantic features and domain knowledge on text categorization

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 […]

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[Sep 23th 2020] LabMeeting: Spectral Clustering with Graph Neural Networks for Graph Pooling

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 […]

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[Sep 16th 2020] LabMeeting: SAILenv: Learning in Virtual Visual Environments Made Simple

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 […]

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[Jul 22nd 2020] LabMeeting: Partial Distance Correlation for Exploring Dependence Between Similarity Networks

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 […]

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[Jul 15th 2020] LabMeeting: Can Domain Knowledge Alleviate Adversarial Attacks in Multi-Label Classifiers?

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 […]

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SAILenv

SAILenv is a Virtual Environment powered by Unity3D. It includes 3 pre-built scenes with full pixel-wise annotations. SAILenv is capable of generating frames at real-time speed, complete with pixel-wise annotations, optical flow and depth. SAILenv also comes with a Python API, designed to easily integrate with the most common learning frameworks available. Pixel-wise Annotations SAILenv […]

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[July 1st 2020] LabMeeting: Next Segment Prediction

Lisa Graziani (University of Florence) Jul 1, 2020 – 11:00 AM Conference Meeting Description In general sketches are generated using generative adversarial models. We propose a new approach which represents the sketches as sequences of segments. This means that segments are ordered with respect to time, so we organize them considering a predefi ned criterion. We […]

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[Jun 24th 2020] LabMeeting: mCSM-membrane: predicting the effects of mutations on transmembrane proteins

Anna Visibelli (University of Siena) Jun 24, 2020 – 11:00 AM Conference Meeting Description Significant efforts have been invested into understanding and predicting the molecular consequences of mutations in protein coding regions, however nearly all approaches have been developed using globular, soluble proteins. These methods have been shown to poorly translate to studying the effects […]

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