Abstract: The efficiency of neural network computations is heavily influenced by numerical precision management. Traditional floating-point (FP) representations offer high precision but are ...
Abstract: Training Deep Neural Networks (DNNs) can be computationally demanding, particularly when dealing with large models. Recent work has aimed to mitigate this computational challenge by ...
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