Difference between revisions of "Fairness Without Demographics in Repeated Loss Minimization"

From statwiki
Jump to: navigation, search
(Risk Bounding Over Unknown Groups)
(Risk Bounding Over Unknown Groups)
Line 15: Line 15:
 
==Risk Bounding Over Unknown Groups==
 
==Risk Bounding Over Unknown Groups==
  
At this point our goal is to minimize the worst-case group risk over a single time-step <math display="inline">\mathcal{R} </math>
+
At this point our goal is to minimize the worst-case group risk over a single time-step <math display="inline">\mathcal{R}_{max} (\theta^{(t)}) </math>.

Revision as of 15:16, 19 October 2018

This page contains the summary of the paper "Fairness Without Demographics in Repeated Loss Minimization" by Hashimoto, T. B., Srivastava, M., Namkoong, H., & Liang, P. which was published at the International Conference of Machine Learning (ICML) in 2018. In the following, an

Overview of the Paper

Introduction

Fairness

Example and Problem Setup

Why Empirical Risk Minimization (ERM) does not work

Distributonally Robust Optimization (DRO)

Risk Bounding Over Unknown Groups

At this point our goal is to minimize the worst-case group risk over a single time-step [math]\mathcal{R}_{max} (\theta^{(t)}) [/math].