Cross-layer approaches for improving the dependability of deep learning systems
Published: May 25, 2020
Abstract
Deep Neural Networks (DNNs) - the state-of-the-art computational models for many Artificial Intelligence (AI) applications - are inherently compute and resource-intensive and, hence, cannot exploit traditional redundancy-based fault mitigation techniques for enhancing the dependability of DNN-based systems. Therefore, there is a dire need to search for alternate methods that can improve their reliability without high expenditure of resources by...
Paper Details
Title
Cross-layer approaches for improving the dependability of deep learning systems
Published Date
May 25, 2020
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