Recently, a research team led by Prof. Zhao Bangchuan from the Institute of Solid State Physics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, in collaboration with Prof. Xiao Yao ...

Abstract: Federated Learning (FL) is an emerging computing paradigm to collaboratively train Machine Learning (ML) models across multi-source data while preserving privacy. The major challenge of ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

Researchers at Central South University in China have developed a new model to improve ultra-short-term photovoltaic (PV) power prediction, as detailed in their publication in Frontiers in Energy. In ...

ABSTRACT: Accurate prediction of survey response rates is essential for optimizing survey design and ensuring high-quality data collection. Traditional methods often struggle to capture the complexity ...

A new study published in the Journal of Orthopaedic Research indicates that an artificial intelligence–based model trained on basic blood and lab test data as well as basic demographic data can ...

Using machine learning models, researchers at Michigan Medicine have identified a potential way to diagnose amyotrophic lateral sclerosis, or ALS, earlier from a blood sample, a study suggests.

In 2025, the Instagram algorithm has become more advanced than ever, using artificial intelligence and machine learning to decide what content users see in their Feeds, Reels, Stories, Explore pages, ...

Designed to accelerate advances in medicine and other fields, the tech giant’s quantum algorithm runs 13,000 times as fast as software written for a traditional supercomputer. A quantum computer at ...

Abstract: This research aims to formulate an optimal control algorithm for a hydrothermal air-conditioning system, with the objective of minimizing energy consumption while simultaneously ensuring ...