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Federal University of Rio Grande do Sul (UFRGS) -Institute of Informatics -PPGC -PGMICRO, Center for Embedded Devices and Research in Digital Agriculture (CEDRA)
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Cumulative bit-flips can drastically alter predictions in quantized neural networks, but SPINE reveals how to strategically harden models against these vulnerabilities.
Adaptive strategies for selecting update algorithms can drastically enhance the performance of probabilistic processors in solving complex optimization problems.
