The SmartData@PoliTO center focuses on Big Data technologies, Data Science and Machine Learning approaches.
We blend interdisciplinary people and competences from different domains to provide cross-domain solutions to the widest spectrum of knowledge discovery challenges, by leveraging advanced expertise in data science, from data management, to data modeling, analytics, and engineering.
We are a well-recognized center where experts in methodologies and domain experts from various disciplines work in a single space, facing both theoretical problems and helping companies toward applications.
Presenter: Giovanni LivragaMonday, February 26th, 2024 5:30 PMLocation: Sala Grande Covivio, Corso Ferrucci 112 ABSTRACT Supporting data owners in maintaining full control over their data is a key requirement in scenarios characterized by outsourcing and/or sharing. Not only does it facilitate compliance with regulations and ethical standards – it can also serve as an enabler […]
Neuro-Symbolic AI Advancements in Computer Vision: A Comprehensive Exploration through Logic Tensor NetworkPresenter: Alessandro RussoMonday, February 12th, 2024 5:30 PMLocation: Sala Piccola Covivio, Corso Ferrucci 112 ABSTRACT In recent years, Neuro-Symbolic AI (NeSy) techniques, particularly within the Logic Tensor Networks (LTN) framework, have driven significant advancements in Computer Vision by integrating symbolic reasoning within neural networks. This hybrid paradigm holds promise for solving intricate real-world problems involving […]
In the following post, we offer the data and the code to replicate the figures regarding CMP adoption included in the paper “Consent Management Platforms: Growth and Users’ Interactions over Time“, currently under revision. In summary, the paper shows how Consent Management Platforms have become popular in the last 9 years, and are nowadays used […]
Presenter: Pierrick LeroyMonday, January 29th, 2024 5:30 PMLocation: Sala Grande Covivio, Corso Ferrucci 112 ABSTRACT A trained (deep) learning model is a sequence of maps and spaces. Data, old and new, are mapped through the model strata from input to output. The main ingredients are a training set of samples from an unknown distribution, a […]