Neural networks made from photonic chips can be trained using on-chip backpropagation – the most widely used approach to training neural networks, according to a new study. The findings pave the way ...
In a Nature Communications study, researchers from China have developed an error-aware probabilistic update (EaPU) method that aligns memristor hardware's noisy updates with neural network training, ...
A new technical paper titled “Hardware implementation of backpropagation using progressive gradient descent for in situ training of multilayer neural networks” was published by researchers at ...
The hype over Large Language Models (LLMs) has reached a fever pitch. But how much of the hype is justified? We can't answer that without some straight talk - and some definitions. Time for a ...
Department of Health and Aging Australia. The Review of the AR-DRG Classification System Development Process: Brisbane, QLD, Australia: PricewaterhouseCoopers; 2009. 2. Klein-Hitpass U, ...
This week at the MLSys Conference in Austin, Texas, researchers from Rice University in collaboration with Intel Corporation announced a breakthrough deep learning algorithm called SLIDE (sub-linear ...
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