Search results for "Fault Tolerance"

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Node co-activations as a means of error detection : Towards fault-tolerant neural networks

2022

Context: Machine learning has proved an efficient tool, but the systems need tools to mitigate risks during runtime. One approach is fault tolerance: detecting and handling errors before they cause harm. Objective: This paper investigates whether rare co-activations – pairs of usually segregated nodes activating together – are indicative of problems in neural networks (NN). These could be used to detect concept drift and flagging untrustworthy predictions. Method: We trained four NNs. For each, we studied how often each pair of nodes activates together. In a separate test set, we counted how many rare co-activations occurred with each input, and grouped the inputs based on whether its class…

machine learningkoneoppiminenerror detectionvirheetfault toleranceneuroverkotneural networksconcept driftluotettavuusdependability
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