ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...

Agent memory remains a problem that enterprises want to fix, as agents forget some instructions or conversations the longer they run. Anthropic believes it has solved this issue for its Claude Agent ...

In the field of multi-objective evolutionary optimization, prior studies have largely concentrated on the scalability of objective functions, with relatively less emphasis on the scalability of ...

Abstract: Multi-party multi-objective optimization, which aims to find a solution set that satisfies multiple decision makers (DMs) as much as possible, has attracted the attention of researchers ...

Meningiomas are the most common primary brain tumors, accounting for nearly one-third of all central nervous system (CNS) tumors. While most are benign and manageable, 20–30% progress to high-grade ...

A new technical paper titled “THERMOS: Thermally-Aware Multi-Objective Scheduling of AI Workloads on Heterogeneous Multi-Chiplet PIM Architectures” was published by researchers at the University of ...

1 Department of Civil Engineering, King Saud University, Riyadh, Saudi Arabia 2 Department of Civil, Materials, and Environmental Engineering, The University of Illinois Chicago, Chicago, IL, United ...

Abstract: Multiobjectivization has emerged as a new promising paradigm to solve single-objective optimization problems (SOPs) in evolutionary computation, where an SOP is transformed into a ...

ABSTRACT: This review focuses on the recent advancements in neuroimaging enabled by deep learning techniques, specifically highlighting their applications in brain disorder detection and diagnosis.