Sparse Maximal Update Parameterization (SμPar): Optimizing Sparse Neural Networks for Superior Training Dynamics and Efficiency Aswin Ak Artificial Intelligence Category – MarkTechPost
[[{“value”:” Sparse neural networks aim to optimize computational efficiency by reducing the number of active weights in the model. This technique is vital as it addresses the escalating computational costs associated with training and inference in deep learning. Sparse networks enhance performance without dense connections,… Read More »Sparse Maximal Update Parameterization (SμPar): Optimizing Sparse Neural Networks for Superior Training Dynamics and Efficiency Aswin Ak Artificial Intelligence Category – MarkTechPost