Abstract: A fast gradient-descent (FGD) method is proposed for far-field pattern synthesis of large antenna arrays. Compared with conventional gradient-descent (GD) methods for pattern synthesis where ...

If it feels like social platforms suddenly “get” you more than they used to, you’re not imagining it! In 2026, feeds aren’t only reacting to what you click anymore. They’re predicting what you ...

Abstract: Distributed gradient descent algorithms have come to the fore in modern machine learning, especially in parallelizing the handling of large datasets that are distributed across several ...

An interesting application of gradient descent aims to stabilize any input graph such that the forces applied on each node are minimum and the overall model is stable. Visualization is perform using ...

"### Gradient descent is an algorithm used to the find local minima of any differentiable function. More formally, given a differentiable function $f(x),$ the ...