7 citations · 7 across the 3 of their papers we have counts for
4 papers
Algorithmic Fairness Over Time: Advances & Prospects
Miriam Rateike
In the presence of feedback loops, algorithmic decisions at one time step can influence observed data in subsequent steps, potentially introducing selection bias or shifts in data…
Designing Long-term Group Fair Policies in Dynamical Systems
Miriam Rateike, Isabel Valera, Patrick Forré
Neglecting the effect that decisions have on individuals (and thus, on the underlying data distribution) when designing algorithmic decision-making policies may increase inequaliti…
Don't Throw it Away! The Utility of Unlabeled Data in Fair Decision Making
Miriam Rateike, Ayan Majumdar, Olga Mineeva +2
Decision making algorithms, in practice, are often trained on data that exhibits a variety of biases. Decision-makers often aim to take decisions based on some ground-truth target…
VACA: Design of Variational Graph Autoencoders for Interventional and Counterfactual Queries
Pablo Sanchez-Martin, Miriam Rateike, Isabel Valera
In this paper, we introduce VACA, a novel class of variational graph autoencoders for causal inference in the absence of hidden confounders, when only observational data and the ca…