Numerical Optimization and Machine Learning

数值优化和机器学习

• 批准号: 544900-2019
• 负责人: LeDigabel, Sébastien
• 金额: $ 18.98万
• 依托单位: École Polytechnique de Montréal
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=699850
• 关键词: Numerical; Optimization; Machine; Learning

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.

华为是电信基础设施和智能设备的全球领导者。该公司大量参与了AI，并且面临与机器学习技术优化有关的几个问题。该项目是华为加拿大华为与蒙特利尔理工学院的四位教授之间的合作，并具有数值优化方面的多元化专业知识。通过将这些专业知识带入机器学习工业应用中，其目的是提高有关数值优化的知识，开发和传播专门用于机器学习的优化工具，并培训高度合格的人员意识到这些问题。在三年中，该项目支持六名博士学位学生，两个博士后研究员，十四个本科实习生和两名研究伙伴。监督遵循层次结构，该结构围绕研究助理，过去被证明是成功的。算法及其相关理论是在Gerad研究中心开发的。它们是由工业合作伙伴的动机，但被设计为可以使其他应用程序受益的通用工具。代码和软件包由学生开发，并由两个专业研究协会验证。一旦足够成熟，它们就会与华为工程师合作对应用进行测试。这项研究的预期结果是改进现有优化方法，更好地适应机器学习工业应用的新算法以及更好的神经网络优化技术。新方法在科学出版物中进行了描述，并且软件包以其通用版本公开提供。该项目在优化领域和机器学习领域都促进了蒙特利尔的国际声誉，这对加拿大来说是高度战略意义的。通过与一家国际公司合作，该公司是电信领域的领导者之一，在AI中，研究人员获得了技术优势，使他们能够开发更高级的方法和培训人员，这对于加拿大就业市场非常需要。最后，该项目的所有方面都遵循公平，多样性和包容性的原则。