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 ...

They can’t guarantee future health, but they can tell you the trajectory you’re on. By Dana G. Smith Take a minute to consider the last decade of your life. What type of physical shape do you hope to ...

Learn how gradient descent really works by building it step by step in Python. No libraries, no shortcuts—just pure math and code made simple. FBI releases new details on suspect in Nancy Guthrie ...

ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...

Check the paper on ArXiv: FastBDT: A speed-optimized and cache-friendly implementation of stochastic gradient-boosted decision trees for multivariate classification Stochastic gradient-boosted ...

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 ...

Abstract: Convolutional neural network is the most important algorithm in the field of deep learning. The traditional convolution neural network usually uses Sigmoid or Relu as the activation function ...