Publications

Random Isn’t Always Fair: Candidate Set Imbalance & Exposure Inequality in Recommender Systems
A Bower*, K Lum *, T Lazovich, K Yee, L Belli. FAccTRec Workshop at RecSys 2022.
[slides]

Debiasing “Bias” Measurement
K Lum, Y Zhang, A Bower. FAccT 2022.
[4 min talk] [15 min talk] [poster]

Classifying and Reporting Harms on Social Media
A Bower, J Passmore, R Chowdhury, K Lum. The Social Life of Algorithmic Harms, Data and Society Workshop.

Measuring Disparate Outcomes of Recommendation Algorithms with Distributional Inequality Metrics
T Lazovich, L Belli, A Gonzales, A Bower, U Tantipongpipat, K Lum, F Huszar, R Chowdhury. Patterns 2022.

Individually Fair Rankings
A Bower, H Eftekhari, M Yurochkin, and Y Sun. ICLR 2021.
[talk]

Preference Modeling with Context-Dependent Salient Features
A Bower and L Balzano. ICML 2020.
[talk]

Training Individually Fair ML Models With Sensitive Subspace Robustness
M Yurochkin*, A Bower*, and Y Sun. ICLR 2020. Spotlight talk.
[code] [talk]

Debiasing Representations by Removing Unwanted Variation Due to Protected Attributes
A Bower*, L Niss*, Y Sun*, and A Vargo*. FAT-ML workshop at ICML 2018.
[code]

The Landscape of Nonconvex Quadratic Feasibility
A Bower, L Jain, L Balzano. ICASSP 2018. Selected for an oral presentation.
[slides]

Fair Pipelines
A Bower*, S Kitchen*, L Niss*, M Strauss*, A Vargo*, and S Venkatasubramanian*. FAT-ML workshop at KDD 2017.

* = equal contribution