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cs.LG2023
Probabilistic computation and uncertainty quantification with emerging covariance
Hengyuan Ma, Yang Qi, Li Zhang +2
Building robust, interpretable, and secure AI system requires quantifying and representing uncertainty under a probabilistic perspective to mimic human cognitive abilities. However…
cs.LG2022
Clustering by the Probability Distributions from Extreme Value Theory
Sixiao Zheng, Ke Fan, Yanxi Hou +2
Clustering is an essential task to unsupervised learning. It tries to automatically separate instances into coherent subsets. As one of the most well-known clustering algorithms, k…