Ranking-based-Instance-Selection
Code for the article "Confidence Scores Make Instance-dependent Label-noise Learning Possible", ICML'21
Github repo for webly labeled learning of sound events
A Light CNN for Deep Face Representation with Noisy Labels, TIFS 2018
Q. Yao, H. Yang, B. Han, G. Niu, J. Kwok. Searching to Exploit Memorization Effect in Learning from Noisy Labels. ICML 2020
automl-4paradigm/s2e 的主要功能包括：Robust Learning Frameworks。
automl-4paradigm/s2e 的开源替代品包括： alibaba-edu/ranking-based-instance-selection — Ranking-based-Instance-Selection. antoninbrthn/csidn — Code for the article "Confidence Scores Make Instance-dependent Label-noise Learning Possible", ICML'21. anuragkr90/webly-labeled-sounds — Github repo for webly labeled learning of sound events. arghosh/robustmw-net — WACV'21: Do We Really Need Gold Samples for Sample Weighting Under Label Noise? awasthiabhijeet/learning-from-rules — Implementation of experiments in paper "Learning from Rules Generalizing Labeled Exemplars" to appear in ICLR2020… alfredxiangwu/lightcnn — A Light CNN for Deep Face Representation with Noisy Labels, TIFS 2018.