Abstract: Analog in-memory computing is a next-generation computing paradigm that promises fast, parallel, and energy-efficient deep learning training and transfer learning (TL). However, achieving ...
Abstract: The performance of artificial neural networks heavily depends on the optimization of network parameters, specifically weights and biases, during the ...
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