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领域的全球领导者。该公司大量参与人工智能，并面临着与机器学习技术优化相关的几个问题。该项目是华为加拿大公司与蒙特利尔理工大学四位教授的合作，他们在数值优化方面具有多样化的专业知识。通过将这些专业知识引入机器学习工业应用，其目的是推进数值优化知识，开发和传播专门用于机器学习的优化工具，并培养了解这些问题的高素质人才。在三年的时间里，该项目支持了六名博士生，两名博士后研究员，十四名本科实习生和两名研究助理。监督遵循围绕研究助理的等级结构，这在过去被证明是成功的。算法及其相关理论在GERAD研究中心开发。它们是由工业合作伙伴驱动的，但被设计为通用工具，可以使其他应用受益。代码和软件包由学生开发并由两位专业研究助理验证。一旦足够成熟，他们将与华为的工程师合作进行应用测试。这项研究的预期成果是改进现有的优化方法，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。科学出版物中介绍了新方法，软件包的通用版本已公开提供。该项目为蒙特利尔在优化和机器学习领域的国际声誉做出了贡献，这两个领域对加拿大具有高度战略意义。通过与一家在电信和人工智能领域处于领先地位的国际公司合作，研究人员获得了技术优势，使他们能够开发更先进的方法，并培训加拿大就业市场非常需要的人员。最后，该项目的所有方面都遵循公平、多样性和包容性原则。