71 citations · 120 across the 9 of their papers we have counts for
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cs.LG2020
SURF: Improving classifiers in production by learning from busy and noisy end users
Joshua Lockhart, Samuel Assefa, Ayham Alajdad +3
Supervised learning classifiers inevitably make mistakes in production, perhaps mis-labeling an email, or flagging an otherwise routine transaction as fraudulent. It is vital that…
cs.LG2020★ 2 cited
Some people aren't worth listening to: periodically retraining classifiers with feedback from a team of end users
Joshua Lockhart, Samuel Assefa, Tucker Balch +1
Document classification is ubiquitous in a business setting, but often the end users of a classifier are engaged in an ongoing feedback-retrain loop with the team that maintain it.…