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Attention dynamics on the Chinese social media Sina Weibo during the COVID-19...
COVID-19 was first detected in Hubei province of China and has had severe impact on the life in the country since then. We investigate how this epidemic has influenced...-
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Private traits and attributes are predictable from digital records of human b...
We show that easily accessible digital records of behavior, Facebook Likes, can be used to automatically and accurately predict a range of highly sensitive personal attributes... -
Beyond Distributive Fairness in Algorithmic Decision Making
Beyond Distributive Fairness in Algorithmic Decision Making Feature Selection for Procedurally Fair Learning With widespread use of machine learning methods in numerous... -
Spatio temporal visual analytics a vision for 2020s
Visual analytics is a research discipline that is based on acknowledging the power and the necessity of the human vision, understanding, and reasoning in data analysis and...-
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Measuring What Counts The case of Rumour Stance Classification
Stance classification can be a powerful tool for understanding whether and which users believe in online rumours. The task aims to automatically predict the stance of replies...-
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Fairer machine learning in the real world
Mitigating discrimination without collecting sensitive data Decisions based on algorithmic, machine learning models can be unfair, reproducing biases in historical data used... -
Why Are Learned Indexes So Effective
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 trends... -
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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Social Network Analysis
Social Network Analysis course @ Master SoBigData This course introduces students to the theories, concepts and measures of Social Network Analysis (SNA), that is aimed at...-
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Complex Network Analysis Lecture
These slides are for a lecture “Network analysis”, of 851-0585-38L Data Science in Techno-Socio-Economic Systems course presented in the spring semester 2021 at ETH Zurich....-
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Tutorial on Learning To Rank
Efficiency/Effectiveness Trade-offs in Learning to Rank” tutorial by Claudio Lucchese and Franco Maria Nardini at the European Conference on Machine Learning and Principles...-
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Data Journalism and Story Telling
The module aims to teach how to present the knowledge extracted from big data using multimedia story telling. It also shows some of the most recent and meaningful experiences...-
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The Role of the GDPR in Designing the European Strategy on Artificial Intelli...
Starting from an analysis of the EU Reg. n. 2016/679 on General Data Protection Regulation (GDPR), the Author deals with the opportunity to translate the current strategies on...-
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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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Big Data and Due Process Toward a Framework to Redress Predictive Privacy Harms
The rise of “Big Data” analytics in the private sector poses new challenges for privacy advocates. Through its reliance on existing data and predictive analysis to create... -
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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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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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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