Abstract: We present a novel second-order trajectory optimization algorithm based on Stein Variational Newton's Method and Maximum Entropy Differential Dynamic Programming. The proposed algorithm, ...

Understand and implement the RMSProp optimization algorithm in Python. Essential for training deep neural networks efficiently. #RMSProp #Optimization #DeepLearning Denmark facing "decisive moment" ...

1 Guangdong Power Grid Corporation Foshan Power Supply Bureau, Foshan, China 2 Electric Power Research Institute of China Southern Power Grid, Guangzhou, Guangdong, China Introduction: The escalating ...

Supply chain partners often face a fundamental trade-off: dishonesty can provide immediate rewards, but excessive lying erodes credibility and undermines future opportunities. Prior research has ...

McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States Oden Institute for Computational Engineering and Sciences, The University of Texas at ...

A cutting-edge reinforcement learning system for optimizing sports sponsorship strategies using hierarchical multi-modal learning with computer vision, NLP, and graph neural networks.

Abstract: dynamic multiobjective optimization (DMO) problems are prevalent in many practical applications and have garnered significant attention from both industry and academia, leading to the ...

ABSTRACT: In the face of growing concerns over environmental sustainability, green software engineering has emerged as a crucial discipline within cloud computing to reduce energy consumption and ...