FPMCO decomposes multi-constraint RL into KL-projection sub-problems, achieving higher reward with lower computing than second-order rivals on the new SCIG robotics benchmark.

The partnership extension builds on a successful collaboration focused on helping operators move beyond traditional CRM and rule-based decisioning Extending our partnership with SCCG is a natural next ...

This project allows users to work with advanced portfolio optimization using natural language, without writing code. It provides 9 specialized MCP tools covering everything from classic mean-variance ...

Operations research (OR) and machine learning (ML) techniques, when used in isolation, are often inadequate for addressing complex optimization problems. While OR struggles with combinatorial ...

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...

Los Angeles, CA, Oct. 14, 2025 (GLOBE NEWSWIRE) -- Aether Pro Exchange has announced a major technological advancement in its trading infrastructure through the integration of adaptive ...

Background: The diagnosis-related groups prospective payment system (DRG-PPS) is widely implemented worldwide. Its core components include disease classification and pricing mechanisms. Developing a ...

MLE-STAR (Machine Learning Engineering via Search and Targeted Refinement) is a state-of-the-art agent system developed by Google Cloud researchers to automate complex machine learning ML pipeline ...

AI has entered a new phase. It is no longer just about building larger models or accessing more data. Today’s competition centers on speed, efficiency and innovation. Companies are seeking new tools ...

Abstract: A machine-learning-based framework for antenna shape optimization design is presented, which enables an accelerated design process for antennas. The employment of a self-supervised learning ...