Whitepaper: Accelerate Training of Deep Neural Networks with MemComputing
by Rich Brueckner from High-Performance Computing News Analysis | insideHPC on (#4Z8S6)
"The paper addresses the inherent limitations associated with today's most popular gradient-based methods, such as Adaptive Moment Estimation (ADAM) and Stochastic Gradient Descent (SGD), which incorporate backpropagation. MemComputing's approach instead aims towards a more global and parallelized optimization algorithm, achievable through its entirely new computing architecture."
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