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 ...

Machine learning workflow enables faster, more reliable organic crystal structure prediction

Prediction of crystal structures of organic molecules is a critical task in many industries, especially in pharmaceuticals ...
Frontiers

Brain-Inspired and neurally grounded algorithms in learning and control of advanced robots

In recent years, the field of robotics has undergone significant transformation, driven increasingly by advances in brain-inspired and neurally grounded ...
New Scientist

Analogue computers could train AI 1000 times faster and cut energy use

Computers built with analogue circuits promise huge speed and efficiency gains over ordinary computers, but normally at the ...
IEEE

Influence of Radiative Transfer Model-Based Atmospheric Correction and Dynamic Tie Points on Sea Ice Concentration Retrieval From Near-90 GHz Algorithm With FY-3D MWRI Data

Abstract: Sea ice concentration (SIC) has been monitored with passive microwave (PM) observations for decades. Various techniques have been developed for its improvement. While techniques such as ...