Minimized dummy Cost Function f(x) = x^2 using default values as initial approximation = 1, error tolerance = 0.0001, learning rate = 0.1, gamma = 0.9, beta_1 = 0.9 ...

This study addresses the growing demand for news text classification driven by the rapid expansion of internet information by proposing a classification algorithm based on a Bidirectional Gated ...

and walks through all the necessary steps to create SGD from scratch in Python. Gradient Descent is an essential part of many machine learning algorithms, including neural networks. To understand how ...

This valuable study introduces a self-supervised machine learning method to classify C. elegans postures and behaviors directly from video data, offering an alternative to the skeleton-based ...

In order to obtain more stable solutions, a distributed approximate gradient descent optimization algorithm and conflict resolution mechanism are proposed, which enhances the convergence of our method ...

This study addresses the structural basis of voltage-activation of BK channels using atomistic simulations of several microseconds, to assess conformational changes that underlie both voltage-sensing ...