Energy is no longer a background input but a defining constraint and increasingly, a performance metric, shaping how AI ...

Can one AI system meaningfully improve another without going back to expensive retraining runs? In other words, can our ...

A new technical paper titled “The Quest for Reliable AI Accelerators: Cross-Layer Evaluation and Design Optimization” was ...

Mathematical optimization is built for exploring unique and developing scenarios we've never seen before, to strengthen ...

Leveraging LLMs to Integrate Expert Knowledge into Algorithmic Planning,” presented at the 25th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2026), introduces a hybrid ...

The study addresses heterogeneous UAV cooperative task assignment under complex constraints via an energy learning ...

Abstract: This work presents a novel Digital Twin (DT) framework, integrating state-space analysis with advanced optimization for predictive health monitoring in a two-stage, single-phase ...

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 ...

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 ...

Computational optics represents a shift in approach where optical hardware and computational algorithms are designed to work together, enabling imaging capabilities that surpass those of traditional ...

Department of Intelligent Energy and Industry, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea Department of Intelligent Energy and Industry, Chung-Ang University, 84 ...