1 citations · 1 across the 5 of their papers we have counts for
Showing 2021Show all
2 papers · 1 filter
cs.LG2021★ 1 cited
Rethinking Noisy Label Models: Labeler-Dependent Noise with Adversarial Awareness
Glenn Dawson, Robi Polikar
Most studies on learning from noisy labels rely on unrealistic models of i.i.d. label noise, such as class-conditional transition matrices. More recent work on instance-dependent n…
cs.LG2021
OpinionRank: Extracting Ground Truth Labels from Unreliable Expert Opinions with Graph-Based Spectral Ranking
Glenn Dawson, Robi Polikar
As larger and more comprehensive datasets become standard in contemporary machine learning, it becomes increasingly more difficult to obtain reliable, trustworthy label information…