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There is one robust loss function ρ j associated with each cluster.
A possible choice, for example, is the Huber's robust loss function, with the corresponding influence function [21].
In fact, this model is independent of any particular datum or cluster models and utilizes a robust loss function.
The robust loss function is also proposed to solve the shortcoming of ε-insensitive loss function during handling hybrid noises.
In this study, we introduce a robust loss function, called Brownboost loss, which computes the feature quality and selects the optimal feature subsets to enhance robustness.
Their definition is given by a robust loss function ρ(x) = ln (f(x)), connected with the probability density function f(x) for the sample data x i, i = 1, …, n.
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Müller and Welsh (2005) attributed this partly to non-robust loss function and hence non robust selection criterion and partly to the fact that some of the bootstrap samples may consist almost entirely of outliers.
PHEN/TPM combination therapy provides robust weight loss that is superior to weight loss achievable with either drug alone.
The catalyst proved to be highly stable and robust without loss of the catalytic activity in recycle runs.
We also demonstrated that these evolved controllers were robust to loss of sensory feedback and other peripheral variations.
Rather, it is better to be robust to loss of information at either of the two ends of a potential link [54].
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