This project is a full-stack Artificial Intelligence (AI) Knowledge Graph Vault built with Obsidian. It covers a wide range of areas including machine learning, deep learning, reinforcement learning, ...

Graph optimisation problems encompass a diverse range of challenges aimed at finding optimal or near‐optimal solutions in networks or graphs. These problems are pivotal in areas such as ...

The topology optimization problem focused in this study is first formulated in section 2. Next, the optimization problem is converted into an RL task, and then extracting member features and a ...

We define a graph-based rate optimization problem and consider its computation, which provides a unified approach to the computation of various theoretical limits, including the (conditional) graph ...

The rapid development of wireless communications have driven the need for careful optimization of network parameters to improve network performance and reduce operational cost. Traditional methods, ...

We propose visual analytics with novel graph embedding for evolutionary SNNs to address the challenges. Even though evolutionary algorithms (EAs) have been shown to promise to optimize SNNs, ...

The talk focuses on expander graphs in conjunction with the combined use of SDPs and eigenvalue techniques for approximating optimal solutions to combinatorial optimization problems. In the first part ...

Using Trace, we develop a general LLM-based generative optimizer called OptoPrime. In empirical studies, we find that OptoPrime is capable of first-order numerical optimization, prompt optimization, ...