A research group has developed SPACIER, an advanced polymer material design tool that integrates machine learning with ...

Quantum researchers from CSIRO, Australia's national science agency, have demonstrated the potential for quantum computing to ...

With a Master's in Computer Science from Clemson University and extensive experience at leading tech companies, he combines ...

Intelligent Network Optimization represents a significant leap forward in network management, offering unparalleled benefits ...

Announcing a new publication for Acta Materia Medica journal. The binding affinity of aptamers to targets has a crucial role in the pharmaceutical and biosensing effects. Despite diverse ...

Santhosh Kumar Shankarappa Gotur's systematic approach to performance testing and optimization provides a robust framework ...

The KAIST team employed the multi-objective Bayesian optimization machine learning algorithm. This algorithm learned from simulated geometries to predict the best possible geometries for enhancing ...

To this end, a HO type prediction and parameter optimization method based on machine learning is proposed. First, the HO is divided into four categories: successful handover (SHO), ping-pong handover ...

Impact Statement: Bi-level Optimization (BLO) has emerged as a compelling approach in machine learning, offering a hierarchical solution to complex optimization challenges. However, conventional BLO ...

This project is part of my Master's thesis and focuses on improving LTE network performance by predicting and optimizing key performance indicators (KPIs) using machine learning models. The study ...