In order to understand currents, tides and other ocean dynamics, scientists need to accurately capture sea surface height, or ...
Transverse tubules (T-tubules) play a significant role in muscle contraction. However, the underlying mechanism of their ...
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Linear regression using gradient descent explained simply
Understand what is Linear Regression Gradient Descent in Machine Learning and how it is used. Linear Regression Gradient ...
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 the ...
ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. There is a need for design strategies that can support rapid and widespread deployment ...
This study introduced an efficient method for solving non-linear equations. Our approach enhances the traditional spectral conjugate gradient parameter, resulting in significant improvements in the ...
All the tech we rely on, from cars to smartphones, was engineered using physics. You don’t need to know the science to use these things. But a well-rounded human should understand at least some of the ...
Jeremy has more than 2200 published articles on Collider to his name, and has been writing for the site since February 2022. He's an omnivore when it comes to his movie-watching diet, so will gladly ...
Abstract: In this paper we propose a novel distributed gradient-based two-time-scale algorithm for multi-agent off-policy learning of linear approximation of the optimal action-value function ...
Background Early diastolic intraventricular pressure gradients (IVPGs) have been proposed to relate to left ventricular (LV) elastic recoil and early ventricular “suction.” Animal studies have ...
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