Limitations of statistical and causal notions of fairness

Chris Hays

How the definitions of social groups matter for mathematically formalizing fairness.

Big data "summaries" can speed up regression on panel data — and reduce the risks of data breaches

Chris Hays

Coresets can efficiently represent data for common statistics and machine learning algorithms; a new paper shows how to construct them for regressions on panel data.

Disentangling the market dynamics of GDPR, EU’s data privacy legislation

Chris Hays

A novel model of the GDPR in personal data driven markets nuances the debate about business interests and consumer privacy.

Debiasing data: An efficient framework using the principle of maximum entropy

Chris Hays

An old idea from statistical physics leads to a new algorithm for mitigating societal biases in data.