Remote Sensing-Based Assessment of Economic Development

The goal of our project is to use satellite data (including nighttime light data and remote sensing images) to give us some statistical estimation of the economic development level of a selected area (Singapore). Findings from the project could inform policymakers about areas needing intervention or support for economic development initiatives. Insights gained might aid in targeted policy formulation for infrastructure, agriculture, urban planning, or resource management.

Approximate Frank-Wolfe Algorithm over Graph-structured Support Set

In this project, we reviewed a paper that deals graph-structured convex optimization (GSCO) problem with the approximate Frank-Wolfe (FW) algorithm. We analyzed and implemented the original algorithm and introduced some extensions based on that. Then we conducted experiments to compare the results and concluded that our backtracking line-search method effectively reduced the number of iterations, while our new DMO method (Top-g+ optimal visiting) did not make satisfying enough improvements.