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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... -
A comparative study of fairness enhancing interventions in machine learning
Computers are increasingly used to make decisions that have significant impact on people's lives. Often, these predictions can affect different population subgroups... -
Data in soccer: an athletic trainer's point of view
Abstract: This webinar is focused on describing the importance of the data in soccer and in particular on the athletic trainer point of view. Cristoforo Fialetti, an athletic...-
Webloc
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Webloc
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Fair Prediction with Disparate Impact A Study of Bias in Recidivism Predictio...
Recidivism prediction instruments (RPIs) provide decision-makers with an assessment of the likelihood that a criminal defendant will reoffend at a future point in time.... -
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... -
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... -
Will big data algorithms dismantle the foundations of liberalism
In Homo Deus, Yuval Noah Harari argues that technological advances of the twenty-first century will usher in a significant shift in how humans make important life decisions....
