Mini Batch Gradient Descent is an algorithm that helps to speed up learning while dealing with a large dataset. Instead of updating the weight parameters after assessing the entire dataset, Mini Batch ...

Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...

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 ...

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...

Abstract: The gradient descent bit-flipping with momentum (GDBF-w/M) and probabilistic GDBF-w/M (PGDBF-w/M) algorithms significantly improve the decoding performance of the bit-flipping (BF) algorithm ...

Understand what is Linear Regression Gradient Descent in Machine Learning and how it is used. Linear Regression Gradient Descent is an algorithm we use to minimize the cost function value, so as to ...

Researchers at Karolinska Institutet and KTH have developed a computational method that can reveal how cells change and specialize in the body. The study, which has been published in the journal PNAS, ...

One day in November, a product strategist we’ll call Michelle (not her real name), logged into her LinkedIn account and switched her gender to male. She also changed her name to Michael, she told ...