5 citations · 8 across the 4 of their papers we have counts for
4 papers
Adaptive Adversarial Training Does Not Increase Recourse Costs
Ian Hardy, Jayanth Yetukuri, Yang Liu
Recent work has connected adversarial attack methods and algorithmic recourse methods: both seek minimal changes to an input instance which alter a model's classification decision.…
Towards User Guided Actionable Recourse
Jayanth Yetukuri, Ian Hardy, Yang Liu
Machine Learning's proliferation in critical fields such as healthcare, banking, and criminal justice has motivated the creation of tools which ensure trust and transparency in ML…
Fairness Improves Learning from Noisily Labeled Long-Tailed Data
Jiaheng Wei, Zhaowei Zhu, Gang Niu +4
Both long-tailed and noisily labeled data frequently appear in real-world applications and impose significant challenges for learning. Most prior works treat either problem in an i…
Unintended Selection: Persistent Qualification Rate Disparities and Interventions
Reilly Raab, Yang Liu
Realistically -- and equitably -- modeling the dynamics of group-level disparities in machine learning remains an open problem. In particular, we desire models that do not suppose…