135 citations · 262 across the 3 of their papers we have counts for
4 papers
Normalized Loss Functions for Deep Learning with Noisy Labels
Xingjun Ma, Hanxun Huang, Yisen Wang +3
Robust loss functions are essential for training accurate deep neural networks (DNNs) in the presence of noisy (incorrect) labels. It has been shown that the commonly used Cross En…
Ground Truth Bias in External Cluster Validity Indices
Yang Lei, James C. Bezdek, Simone Romano +3
It has been noticed that some external CVIs exhibit a preferential bias towards a larger or smaller number of clusters which is monotonic (directly or inversely) in the number of c…
Adjusting for Chance Clustering Comparison Measures
Simone Romano, Nguyen Xuan Vinh, James Bailey +1
Adjusted for chance measures are widely used to compare partitions/clusterings of the same data set. In particular, the Adjusted Rand Index (ARI) based on pair-counting, and the Ad…
A Framework to Adjust Dependency Measure Estimates for Chance
Simone Romano, Nguyen Xuan Vinh, James Bailey +1
Estimating the strength of dependency between two variables is fundamental for exploratory analysis and many other applications in data mining. For example: non-linear dependencies…