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  • TrainingMaterial

    Social Network Analysis @MasterBigData2022

    This course introduces students to the theories, concepts, and measures of Social Network Analysis (SNA), which is aimed at characterizing the structure of large-scale Online...
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  • JournalArticle

    UTLDR: an agent-based framework for modelling infectious diseases and public ...

    Nowadays, due to the SARS-CoV-2 pandemic, epidemic modeling is experiencing a constantly growing interest from researchers of heterogeneous fields of study. Indeed, the vast...
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  • ConferencePaper

    A Learned Approach to Quicken and Compress Rank Select Dictionaries

    We introduce the first “learned” scheme for implementing a compressed rank/select dictionary. We prove theoretical bounds on its time and space performance both in the worst...
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  • TrainingMaterial

    Evaluating the significance of network observables with a maximum entropy-bas...

    This webinar was organised by the Network Medicine Exploratory (WP10) and hosted Enrico Maiorino. Enrico Maiorino is a very esteemed researcher at Brigham Women's Hospital,...
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  • TrainingMaterial

    Deep Learning Course

    This course developed by Universitat Politècnica de Catalunya and Barcelona Supercomputing Center provides an applied approach to Deep Learning. It chooses to present an...
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    • ZIP
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    • ZIP
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  • JournalArticle

    Big other Surveillance capitalism and the prospects of an information civiliz...

    This article describes an emergent logic of accumulation in the networked sphere, ‘surveillance capitalism,’ and considers its implications for ‘information civilization.’ The...
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  • TrainingMaterial

    Compressed and Learned Data Structures Seminar

    In this seminar cycle, students are guided in the direct usage of a powerful C++ library implementing many state-of-the-art compressed data structures for big data. Other than...
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    • ZIP
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  • JournalArticle

    Identifying and exploiting homogeneous communities in labeled networks

    Attribute-aware community discovery aims to find well-connected communities that are also homogeneous w.r.t. the labels carried by the nodes. In this work, we address such a...
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  • JournalArticle

    Explaining misclassification and attacks in deep learning via random forests

    Artificial intelligence, and machine learning (ML) in particular, is being used for different purposes that are critical for human life. To avoid an algorithm-based...
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  • JournalArticle

    The democracy of emergency at the time of the coronavirus the virtues of privacy

    The emergency of the Coronavirus imposes a cultural debate on the balancing of rights, freedoms and social responsibilities, finalized to the protection of individual and...
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  • ConferencePaper

    Efficient detection of Byzantine attacks in federated learning using last lay...

    Federated learning (FL) is an alternative to centralized machine learning (ML) that builds a model across multiple decentralized edge devices (a.k.a. workers) that own the...
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  • JournalArticle

    Conformity a Path-Aware Homophily measure for Node-Attributed Networks

    Unveil the homophilic/heterophilic behaviors that characterize the wiring patterns of complex networks is an important task in social network analysis, often approached...
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  • ConferencePaper

    Fair detection of poisoning attacks in federated learning

    Federated learning is a decentralized machine learning technique that aggregates partial models trained by a set of clients on their own private data to obtain a global model....
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