Numerical Optimization and Machine Learning

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Huawei is a worldwide leader in telecommunication infrastructures and smart devices. The company is massively involved in AI and faces several issues related to the optimization in machine learning techniques. This project is a collaboration between Huawei Canada and four professors of Polytechnique Montréal with a diversified expertise in numerical optimization. By bringing this expertise into machine learning industrial applications, its aim is to advance knowledge on numerical optimization, to develop and disseminate optimization tools specialized for machine learning, and to train highly-qualified personnel aware of these issues. During three years, this project supports six PhD students, two postdoctoral fellows, fourteen undergraduate interns, and two research associates. Supervisions follow a hierarchical structure that revolves around the research associates and that has been proved successful in the past. Algorithms and their associated theory are developed at the GERAD research center. They are motivated by the industrial partner but are designed as generic tools that can benefit other applications. Codes and software packages are developed by students and validated by the two professional research associates. Once mature enough, they are tested on the applications in collaboration with Huawei's engineers. The anticipated outcomes of this research are the improvement of existing optimization methods, new algorithms that are better adapted to machine learning industrial applications, and better neural networks optimization techniques. The new methods are described in scientific publications and the software packages are made publicly available in their generic versions. This project contributes to the international reputation of Montréal in both fields of optimization and machine learning, which are highly strategic for Canada. By teaming up with an international company that is one of the leaders in telecommunications and in AI, researchers gain a technological edge that allows them to develop more advanced methods and train personnel that are highly desirable for the Canadian job market. Finally, all aspects of this project follow the principles of equity, diversity and inclusion.