Abstract: Test optimization selection (TOS) is a crucial technology in testability design, playing a key role in intelligent manufacturing by enhancing product maintainability and reliability while ...

Forecasting, a fundamental task in machine learning, involves predicting future values of a time series based on its historical behavior. This paper introduces a novel Hierarchical Patch Based ...

Discover how multivariate models use multiple variables for investment forecasting, risk analysis, and decision-making in finance. Ideal for portfolio management.

Abstract: This paper addresses the distributed nonconvex optimization problem, where both the global cost function and local inequality constraint function are nonconvex. To tackle this issue, the ...

As global concerns over sustainability grow, integrating advanced mathematical optimization techniques into decision support systems is vital for sustainable supply chain management. Modern supply ...

Objectives In patients with chronic obstructive pulmonary disease (COPD), severe exacerbations (ECOPDs) impose significant morbidity and mortality. Current guidelines emphasise using ECOPD history to ...

This is a reference implementation and will not be actively maintained in the future. The code in this repository is a refactored version of the codebase we used to produce the results in the paper ...