Gradient descent has a fundamental limitation: on most real-world loss surfaces, it is inefficient. When the surface has uneven curvature—steep in one direction and flat in another, which is common in ...

Abstract: We propose an adaptive moment estimation (Adam)-based 2 nd-order Volterra nonlinear equalizer (VNLE) employing a mini-batch gradient descent (MGD) algorithm for intensity ...

Abstract: We propose an adaptive moment estimation (Adam)-based $2^{\mathrm {nd}}$ -order Volterra nonlinear equalizer (VNLE) employing a mini-batch gradient descent (MGD) algorithm for intensity ...

Mini Batch Gradient Descent is an algorithm that helps to speed up learning while dealing with a large dataset. Instead of updating the weight parameters after assessing the entire dataset, Mini Batch ...

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Performing gradient descent for calculating slope and intercept of linear regression using sum square residual or mean square error loss function. A "from-scratch" 2 ...

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