[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 8th 2020] LabMeeting: Generate and Revise:Reinforcement Learning in Neural Poetry

Luca Pasqualini (University of Siena) Jul 8, 2020 – 11:00 AM Conference Meeting Description Writers, poets, singers usually do not create their compositions in just one breath. Text is revisited, adjusted, modified, rephrased, even multiple times, in order to better convey meanings, emotions and feelings that the author wants to express. Amongst the noble written […]

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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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