This study addresses an energy-efficient multiobjective distributed assembly permutation flowshop scheduling problem with sequence dependent setup time. The objectives are to minimize the maximum ...

The deadline is closing in, compiler errors keep flashing across your screen, and the fear of lost GPA points feels like a waking nightmare. In that moment, a s ...

We used DL methods based on images to distinguish pulmonary infections. A machine learning (ML) model for risk interpretation was developed using key imaging (learned from the DL methods) and clinical ...

🎯 We built a beginner-friendly federated learning (FL) library and benchmark: master FL in 2 hours—run it on your PC! Contribute your algorithms, datasets, and metrics to grow the FL community. 👏 ...

Starting with small python projects for beginners like a calculator or a to-do list helps you get comfortable with basic ...

machine-learning-algorithms Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments ...

In network science and the data mining field, a long-lasting and significant task is to predict the propagation capability of nodes in a complex network. Recently, an increasing number of unsupervised ...

A new machine learning approach that draws inspiration from the way the human brain seems to model and learn about the world has proven capable of mastering a number of simple video games with ...