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cs.LG2023
Explicit Foundation Model Optimization with Self-Attentive Feed-Forward Neural Units
Jake Ryland Williams, Haoran Zhao
Iterative approximation methods using backpropagation enable the optimization of neural networks, but they remain computationally expensive, especially when used at scale. This pap…
cs.LG2023
Reducing the Need for Backpropagation and Discovering Better Optima With Explicit Optimizations of Neural Networks
Jake Ryland Williams, Haoran Zhao
Iterative differential approximation methods that rely upon backpropagation have enabled the optimization of neural networks; however, at present, they remain computationally expen…