Machine learning techniques that make use of tensor networks could manipulate data more efficiently and help open the black ...

Abstract: Formalizing complex processes and phenomena of a real-world problem may require a large number of variables and constraints, resulting in what is termed a large-scale optimization problem.

Abstract: Optimal Power Flow (OPF) is a constrained, high-dimensional, non-convex nonlinear programming problem that typically has multiple local optimal solutions. To address the issue where most ...

This repository contains PyTorch implementation of POMO version of ICML 2025 poster -- "Preference Optimization for Combinatorial Optimization Problems". TL;DR: We theoretically transform numerical ...

Morgan Wallen is moving full steam ahead to his next musical project. After releasing his One Thing at a Time album in 2023 and touring to promote the album over the last two years, the country singer ...

Artificial intelligence has witnessed a remarkable surge, captivating researchers, product teams, and end users alike with its transformative potential. But despite its recent popularity, AI is only ...

Modern power systems are developing rapidly, with distributed energy, energy storage devices, adjustable loads, and other flexible resources consolidated through microgrids, virtual power plants, and ...

In this paper, we use partial differential equations to deal with constraint optimal control problems. We construct extremal flows by differential-algebraic equation to approximate the optimal ...

1 State Grid Nanjing Power Supply Company, Information and Communication Branch, Nanjing, China 2 School of Electrical Engineering, Southeast University, Nanjing, China This article presents a study ...

Aligning large language models (LLMs) with human values and preferences is challenging. Traditional methods, such as Reinforcement Learning from Human Feedback (RLHF), have paved the way by ...