In a Nature Communications study, researchers from China have developed an error-aware probabilistic update (EaPU) method that aligns memristor hardware's noisy updates with neural network training, ...

Faculty of Food Technology and Quality Management of Agricultural Products, National University of Life and Environmental Sciences of Ukraine, Kyiv 57207861801, Ukraine ...

ABSTRACT: The stock market faces persistent challenges, including inefficiencies, volatility, and barriers to entry, which hinder its accessibility and reliability for investors. This paper explores ...

Obtaining the gradient of what's known as the loss function is an essential step to establish the backpropagation algorithm developed by University of Michigan researchers to train a material. The ...

Key Laboratory of Biomass Chemical Engineering of Ministry of Education, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China ...

A new technical paper titled “The backpropagation algorithm implemented on spiking neuromorphic hardware” was published by University of Zurich, ETH Zurich, Los Alamos National Laboratory, Royal ...

Natural neural systems have inspired innovations in machine learning and neuromorphic circuits designed for energy-efficient data processing. However, implementing the backpropagation algorithm, a ...

Abstract: The backpropagation (BPN) algorithm is used in artificial neural networks (ANN) for training the networks that uses unsupervised learning and it is performed in two consecutive phases for ...

Nello Cristianini is affiliated with the University of Bath, and the author of two books that cover the topics of this article, The Shortcut (CRC Press, 2023) and Machina Sapiens (Mulino, 2024). We ...