Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe Noise — mentioned by nerdponx

Sun, 22 Aug 2021 22:33:54 GMT

The irony is that there are techniques for dealing with noisy/mislabeled/bad data (e.g. gold loss correction [0], errors-in-variables models [1]), but that stuff isn't "sexy" and not enough practitioners know about it. 0: https://arxiv.org/abs/1802.05300 1: https://en.m.wikipedia.org/wiki/Errors-in-variables_models

Paper and discussion history. A mention is not an endorsement.

Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe Noise · HackerPapers discussions

Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe Noise — mentioned by nerdponx