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NetMe
The huge amount of biological literature, which daily increases, represents a strategic resource to automatically extract and gain knowledge concerning relations among... -
Private ASPen: ASP-based Implementation for Collective Entity Resolution
This is an Answer Set Programming (ASP) encoding for LACE, which is a novel declarative approach to Collective Entity Resolution in the classical relational database setting.... -
CORAL: expert-Curated medical Oncology Reports to Advance Language model infe...
Both medical care and observational studies in oncology require a thorough understanding of a patient's disease progression and treatment history, often elaborately documented... -
OpenAirInterface 5G Dataset: TCP Uplink Traffic Experiment with Two UEs
The dataset comprises logs generated by OpenAirInterface (OAI) at the Medium Access Control (MAC) layer. It consists of a CSV file containing data collected from experiments... -
GLM for BRCA
The dataset comprises labeled genetic variations of the BRCA1 and BRCA2 genes obtained from the ClinVar database. After refining annotations based on quality and completeness... -
Big Data Ethics
The speed of development in Big Data and associated phenomena, such as social media, has surpassed the capacity of the average consumer to understand his or her actions and... -
Democratizing Algorithmic Fairness
Machine learning algorithms can now identify patterns and correlations in (big) datasets and predict outcomes based on the identified patterns and correlations. They can then... -
Designing for human rights in AI
In the age of Big Data, companies and governments are increasingly using algorithms to inform hiring decisions, employee management, policing, credit scoring, insurance... -
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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Fairness and Abstraction in Sociotechnical Systems
A key goal of the fair-ML community is to develop machine-learning based systems that, once introduced into a social context, can achieve social and legal outcomes such as... -
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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Epidemics and city. How mobility and well being changed with COVID19 era
How did the COVID-19 epidemics change our mobility habits, and how did it impact on people’s well-being and on the virus transmissibility? In the first webinar of the seminar...-
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Ethical Value Centric Cybersecurity. A Methodology Based on a Value Graph
Our society is being shaped in a non-negligible way by the technological advances of recent years, especially in information and communications technologies (ICTs). The... -
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... -
Information Technology Privacy and the Protection of Personal Data
Information technology allows us to generate, store, and process huge quantities of data. Search engines, satellites, sensor networks, scientists, security agencies,... -
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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Measuring discrimination in algorithmic decision making
Society is increasingly relying on data-driven predictive models for automated decision making. This is not by design, but due to the nature and noisiness of observational... -
Privacy in the clouds
Informational self-determination refers to the right or ability of individuals to exercise personal control over the collection, use and disclosure of their personal data by... -
Recommender systems and their ethical challenges
This article presents the first, systematic analysis of the ethical challenges posed by recommender systems through a literature review. The article identifies six areas of...
