Conference: Inaugural CAMDA Conference

随着Chat-GPT和Bard等高度通用的大型语言模型的发布，机器学习最近再次引起了人们的关注。随着人们对技术进步的社会和经济影响的担忧越来越多，许多机器学习最成功的工具仍然知之甚少，甚至对它们的创造者来说，它们的内部工作也是模糊的。我们相信，一个健康和持久的社会必须建立在良好理解，负责任和可解释的原则。本次会议致力于机器学习的数学基础及其在可分析环境中的应用，旨在构建工具来更好地理解强大但难以理解的新兴工具，并讨论可解释的替代方法。德克萨斯农工大学是逼近理论的历史据点，逼近理论本身就是学习理论的基础。事实上，问题是"函数一般能近似到什么程度？可以说，在这个问题之前，一个函数可以从点值近似到什么程度？'.本次会议（https：//sites.google.com/tamu.edu/camda-conference/）的目标是将严格的数学分析置于数据科学未来发展的中心，以指导对社会和环境负责的进步。来自数学系，电气和计算机工程系以及计算机科学系的四位全体演讲者将在这一努力中向跨学科的听众发表讲话。一个“开放问题”会议计划讨论和传播的重要开放问题，在这方面的努力，与吸引初级研究人员的具体目标。这一奖项反映了NSF的法定使命，并已被认为是值得通过评估使用基金会的智力价值和更广泛的影响审查标准的支持。

Machine learning has recently attracted renewed attention following the release of highly versatile large language models such as Chat-GPT and Bard. As concerns about the social and economic impact of technical advances mount, many of machine learning's most successful tools remain poorly understood and their inner working obscure even to their creators. We believe that a healthy and durable society must be built on well-understood, responsible, and interpretable principles. This conference is dedicated to the mathematical foundations of machine learning and its application in analytically tractable settings with the aim of building the tools to better understand the powerful, but inscrutable emerging tools and to discuss interpretable alternative approaches.Texas A&M University is a historical stronghold of approximation theory, which itself underlies learning theory. Indeed, the question 'how well can a function be approximated in general?' arguably precedes the question 'how well can a function be approximated from point values?'. It is an objective of this conference (https://sites.google.com/tamu.edu/camda-conference/) to place rigorous mathematical analysis at the center of future developments in data science in order to guide socially and environmentally responsible progress. Four plenary speakers from Departments of Mathematics, Electrical and Computer Engineering and Computer Science will address an interdisciplinary audience in this effort. An 'open problems' session is planned for the discussion and dissemination of important open problems in this effort, with the specific goal of attracting junior researchers.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.