841 citations · 1.8k across the 37 of their papers we have counts for
5 papers · 1 filter
TAPAS: Tricks to Accelerate (encrypted) Prediction As a Service
Amartya Sanyal, Matt J. Kusner, Adrià Gascón +1
Machine learning methods are widely used for a variety of prediction problems. \emph{Prediction as a service} is a paradigm in which service providers with technological expertise…
Blind Justice: Fairness with Encrypted Sensitive Attributes
Niki Kilbertus, Adrià Gascón, Matt J. Kusner +3
Recent work has explored how to train machine learning models which do not discriminate against any subgroup of the population as determined by sensitive attributes such as gender…
Causal Interventions for Fairness
Matt J. Kusner, Chris Russell, Joshua R. Loftus +1
Most approaches in algorithmic fairness constrain machine learning methods so the resulting predictions satisfy one of several intuitive notions of fairness. While this may help pr…
Causal Reasoning for Algorithmic Fairness
Joshua R. Loftus, Chris Russell, Matt J. Kusner +1
In this work, we argue for the importance of causal reasoning in creating fair algorithms for decision making. We give a review of existing approaches to fairness, describe work in…
A Generative Model For Electron Paths
John Bradshaw, Matt J. Kusner, Brooks Paige +2
Chemical reactions can be described as the stepwise redistribution of electrons in molecules. As such, reactions are often depicted using `arrow-pushing' diagrams which show this m…