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ICLR-2021-Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks #332

Open BrambleXu opened 3 years ago

BrambleXu commented 3 years ago

Summary:

有名的数据集(测试集)里结果充满了标注错误。

Resource:

Paper information:

Notes:

被认为是错误的标签要通过confident learning和human两重验证。在被算法认为是错误标签的数据中,发现54%确实是被错误标注的。

该研究发现低复杂度的模型比高复杂度模型在错误标注的数据上效果更好。

Model Graph:

Result:

Thoughts:

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