Modeled on the human brain, neural networks are one of the most common styles of machine learning ... known good answers. This function is known as the error, or loss function.

Abstract: We analyze and contrast two ways to train machine learning models for solving AC optimal power flow (OPF) problems ... between predicted and optimal dispatch decisions as the loss function.

The goal of machine learning is to minimize the loss function, which means finding the optimal parameters of the model that make the predictions as close as possible to the true values.

In a novel study, researchers from the Icahn School of Medicine at Mount Sinai introduced LoGoFunc, an advanced computational tool that predicts pathogenic gain- and loss-of-function variants ...

Abstract: Federated learning (FL) is a communication-efficient machine learning paradigm to leverage distributed ... accuracy due to the proper weights assignments of noisy loss function.

However, obtaining the structure or function of the peptides with wet experiments is costly, laborious, and time-consuming. In recent years, because of the obvious advantages of traditional machine ...

Analysis of pulmonary function tests (PFTs) is an area where machine learning (ML) may benefit clinicians ... ML can also be used to analyze continuous data or the graphics, including the flow-volume ...

In machine learning, one method that has consistently demonstrated ... A research team from Tsinghua University has introduced a Slide loss function to construct an SVM classifier. This innovative ...