5 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.LG2022
iFlipper: Label Flipping for Individual Fairness
Hantian Zhang, Ki Hyun Tae, Jaeyoung Park +2
As machine learning becomes prevalent, mitigating any unfairness present in the training data becomes critical. Among the various notions of fairness, this paper focuses on the wel…
cs.LG2021★ 2 cited
Responsible AI Challenges in End-to-end Machine Learning
Steven Euijong Whang, Ki Hyun Tae, Yuji Roh +1
Responsible AI is becoming critical as AI is widely used in our everyday lives. Many companies that deploy AI publicly state that when training a model, we not only need to improve…
cs.DB2019★ 5 cited
Data Cleaning for Accurate, Fair, and Robust Models: A Big Data - AI Integration Approach
Ki Hyun Tae, Yuji Roh, Young Hun Oh +2
The wide use of machine learning is fundamentally changing the software development paradigm (a.k.a. Software 2.0) where data becomes a first-class citizen, on par with code. As ma…