activity
20192022
most citedLearning Smooth and Fair Representations

3 citations · 11 across the 8 of their papers we have counts for

collaborators

9 papers

cs.LG2022

Ex-Ante Assessment of Discrimination in Dataset

Jonathan Vasquez, Xavier Gitiaux, Huzefa Rangwala

Data owners face increasing liability for how the use of their data could harm under-priviliged communities. Stakeholders would like to identify the characteristics of data that le…

cs.LG2022

SoFaiR: Single Shot Fair Representation Learning

Xavier Gitiaux, Huzefa Rangwala

To avoid discriminatory uses of their data, organizations can learn to map them into a representation that filters out information related to sensitive attributes. However, all exi…

cs.CY2022★ 2 cited

Trade-offs between Group Fairness Metrics in Societal Resource Allocation

Tasfia Mashiat, Xavier Gitiaux, Huzefa Rangwala +2

We consider social resource allocations that deliver an array of scarce supports to a diverse population. Such allocations pervade social service delivery, such as provision of hom…

quant-ph2021★ 1 cited

SWAP Test for an Arbitrary Number of Quantum States

Xavier Gitiaux, Ian Morris, Maria Emelianenko +1

We develop a recursive algorithm to generalize the quantum SWAP test for an arbitrary number of quantum states requiring controlled-swap (CSWAP) gates and an…

cs.LG2021

Fair Representations by Compression

Xavier Gitiaux, Huzefa Rangwala

Organizations that collect and sell data face increasing scrutiny for the discriminatory use of data. We propose a novel unsupervised approach to transform data into a compressed b…

cs.LG2020★ 3 cited

Learning Smooth and Fair Representations

Xavier Gitiaux, Huzefa Rangwala

Organizations that own data face increasing legal liability for its discriminatory use against protected demographic groups, extending to contractual transactions involving third p…