Datasets for the dissertation "Leveraging Data in Algorithm Design"

The contents of this repository are the source code and datasets for each of the chapters of the dissertation by Esther Julien. This dissertation explores the use of machine-learning techniques to improve the performance of various algorithms. These algorithms solve problems appearing within the field of operations research, with a focus on bilevel optimization and adaptable robust optimization, and for the construction of phylogenetic networks. The data consists of source code for each of these projects and data for test instances and self-generated training data for the various supervised machine-learning models.本代码仓库收录了Esther Julien所撰写博士论文各章节对应的源代码与配套数据集。该论文旨在探究机器学习技术在提升各类算法性能上的应用价值。所涉算法可用于解决运筹学领域的各类问题，研究重点涵盖双层优化（bilevel optimization）与自适应鲁棒优化（adaptable robust optimization）方向，同时也应用于系统发育网络（phylogenetic networks）的构建工作。本数据集包含各研究项目的源代码、测试实例数据，以及面向各类监督机器学习模型的自研训练数据。