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Found 4 papers, 1 papers with code
Normalized Loss Functions for Deep Learning with Noisy Labels
However, in practice, simply being robust is not sufficient for a loss function to train accurate DNNs.
Ranked #30 on
Image Classification
on mini WebVision 1.0
(ImageNet Top-1 Accuracy metric)
Ground Truth Bias in External Cluster Validity Indices
For example, NCinc bias in the RI can be changed to NCdec bias by skewing the distribution of clusters in the ground truth partition.
Adjusting for Chance Clustering Comparison Measures
In particular, the Adjusted Rand Index (ARI) based on pair-counting, and the Adjusted Mutual Information (AMI) based on Shannon information theory are very popular in the clustering community.
A Framework to Adjust Dependency Measure Estimates for Chance
For example: non-linear dependencies between two continuous variables can be explored with the Maximal Information Coefficient (MIC); and categorical variables that are dependent to the target class are selected using Gini gain in random forests.
