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Dataset for Evaluating Abstractive Summaries of Crisis-Related Social Media
The dataset created for evaluation of summaries generated from social media posted during five natural disasters. The dataset contains: ground truth reports created by human... -
Private Morningness–eveningness assessment from mobile phone communication analysis
Human behaviour follows a 24-h rhythm and is known to be governed by the individual chronotypes. Due to the widespread use of technology in our daily lives, it is possible to... -
Private Human-agent coordination in a group formation game
Coordination and cooperation between humans and autonomous agents in cooperative games raise interesting questions on human decision making and behaviour changes. Here we report... -
Private Ecology of the digital world of Wikipedia
Wikipedia, a paradigmatic example of online knowledge space is organized in a collaborative, bottom-up way with voluntary contributions, yet it maintains a level of reliability... -
Membership Inference Attacks on ML Models
This collection of Jupyter notebooks implements membership inference attacks found in Salem et al. "ML-Leaks: Model and Data Independent Membership Inference Attacks and... -
What is a meme, technically speaking?
This contribution seeks to demonstrate how studying memes as a collection depends on the website or platform where they are sourced. To do so, we compare how memes,... -
The Propagation of Misinformation in Social Media
There is growing awareness about how social media circulate extreme viewpoints and turn up the temperature of public debate. Posts that exhibit agitation garner... -
How to Make Meme Collections
How to guide to make meme collections by querying and extracting memes from four key sites: the meme database Know Your Meme, the web search engine Google Images, the meme...-
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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 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... -
A Critical Reassessment of the Saerens-Latinne-Decaestecker Algorithm
We critically re-examine the Saerens-Latinne-Decaestecker (SLD) algorithm, a well-known method for estimating class prior probabilities (“priors”) and adjusting posterior... -
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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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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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... -
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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Private Structural Invariants in Individuals Language Use The Ego Network of Words
The cognitive constraints that humans exhibit in their social interactions have been extensively studied by anthropologists, who have highlighted their regularities across... -
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... -
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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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... -
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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