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Estimating mutual information for feature selection in the presence of label noise
Publisher: Elsevier Science
Year: 2014
Label denoising based on Bayesian aggregation
Year: 2016
Abstract:
Label noise is a common problem that affects supervised learning and can produce misleading results. It is shown that only 5% of switched labels lead to a decrease of performances. Therefore, the true class of an instance must be distinguished...
Classification in the Presence of Label Noise: A Survey
Publisher: IEEE
Year: 2014
Simulation of influence of template size on misfit dislocation in nanostructures
Publisher: IEEE
Year: 2014
A Similarity-Based Classification Framework for Multiple-Instance Learning
Publisher: IEEE
Year: 2014
Bitcoin mining acceleration and performance quantification
Publisher: IEEE
Year: 2014
Stochastic Analysis of Epidemic Routing Based Anycast in Throwbox-Equipped DTNs
Publisher: IEEE
Year: 2014