IEEE

MPDA: A Massively Parallel Learning and Dependency-Aware Scheduling Algorithm for Data Processing Clusters

Abstract: In the era of large-scale machine learning, large-scale clusters are extensively used for data processing jobs. However, the state-of-the-art heuristic-based and Deep Reinforcement Learning ...
IEEE

Hybrid Variational Quantum Algorithm Enhanced Subentire-Domain Basis Functions Method With High Learning Efficiency and Better Robustness

Abstract: The subentire-domain (SED) basis functions method is the most effective method for analyzing the electromagnetic (EM) properties of large-scale finite periodic structures (LFPSs). Recently, ...

Which Machine Learning Models Are Most Used In Crypto Signal Generation?

Machine learning is transforming how crypto traders create and understand signals. From supervised models such as Random Forests and Gradient Boosting Machines to sophisticated deep learning hybrids ...
Scientific Research Publishing

Research on Prediction of Air Quality CO Concentration Based on Python Machine Learning ()

Wang, Z. (2025) Research on Prediction of Air Quality CO Concentration Based on Python Machine Learning. Advances in Internet ...