Abstract: In order to address the challenges of unknown initial positions and accumulated long-distance positioning errors in pedestrian dead reckoning (PDR), as well as significant ranging errors ...
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Mini-batch gradient descent in deep learning explained
Mini Batch Gradient Descent is an algorithm that helps to speed up learning while dealing with a large dataset. Instead of ...
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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 ...
Abstract: Hybrid loss minimization algorithms in electrical drives combine the benefits of search-based and model-based approaches to deliver fast and robust dynamic responses. This article presents a ...
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