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Temporal social network reconstruction using wireless proximity sensors: mode...
The emerging technologies of wearable wireless devices open entirely new ways to record various aspects of human social interactions in a broad range of settings. Such...-
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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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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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A theoretical model for pattern discovery in visual analytics
The word ‘pattern’ frequently appears in the visualisation and visual analytics literature, but what do we mean when we talk about patterns? We propose a practicable... -
Angel efficient and effective node centric community discovery in static and ...
Community discovery is one of the most challenging tasks in social network analysis. During the last decades, several algorithms have been proposed with the aim of identifying... -
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... -
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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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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Network generator with fractal topologies - related to WP8
The micro-project has developed a python module for the generation of networks with fractal topologies, in particular Sierpinski graphs for the task involved in T8.4 Complex... -
Ego network analysis, information-driven social links and impact on informati...
Slide from the Summer School on Computational Misinformation Analysis 2019 lesson-
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On the performance of learned data structures
A recent trend in algorithm design consists of augmenting classic data structures with machine learning models, which are better suited to reveal and exploit patterns and... -
Boilerplate Removal using a Neural Sequence Labeling Model
The extraction of main content from web pages is an important task for numerous applications, ranging from usability aspects, like reader views for news articles in web... -
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... -
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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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... -
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... -
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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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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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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