Graph-Based Optimization

Graph-based optimization is a method used to improve the accuracy of data or models by representing them as a network of nodes (points) and edges (connections). Each node contains information, and the connections express relationships or constraints between these points. The process involves adjusting the nodes' values to minimize errors or inconsistencies across the network, resulting in a more accurate overall solution. This approach is commonly used in fields like robotics, computer vision, and mapping, where complex data needs to be refined efficiently by analyzing the structure of the relationships within the graph.