12 citations · 24 across the 18 of their papers we have counts for
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cs.LG2022★ 2 cited
Promises and Pitfalls of Threshold-based Auto-labeling
Harit Vishwakarma, Heguang Lin, Frederic Sala +1
Creating large-scale high-quality labeled datasets is a major bottleneck in supervised machine learning workflows. Threshold-based auto-labeling (TBAL), where validation data obtai…
stat.ML2022★ 1 cited
One for All: Simultaneous Metric and Preference Learning over Multiple Users
Gregory Canal, Blake Mason, Ramya Korlakai Vinayak +1
This paper investigates simultaneous preference and metric learning from a crowd of respondents. A set of items represented by -dimensional feature vectors and paired comparison…