REU Site: Advances of Machine Learning in Theory and Applications (AMALTHEA)

机器学习理论应用进展（AMALTHEA）REU网站旨在通过参与机器学习（ML）领域的研究，为多元化的本科生社区提供高质量的教育体验。ML的相关性和重要性并不像过去那样仅限于专业技术创新。如今，它也越来越多地影响日常生活，通过其对语音/面部识别，信用欺诈检测，智能推荐系统等应用的贡献。此外，机器学习本质上是多学科的，因为它借鉴了计算、统计、数学、物理、生物和工程等学科的进步。该项目的重点领域是ML理论以及如何将其集成并应用于重要的现实问题，从而使参与者了解理论和应用。AMALTHEA每年有10名来自广泛学科的本科生在夏季学习10周。这些参与者进行监督研究，其结果将影响ML本身的领域，以及ML如何应用于其他科学学科。为此，导师们在机器学习方面拥有丰富的专业知识，并有有效地让本科生参与最先进研究的经验。在其生命周期内，该项目将直接影响30名有动力的学生，其中大多数人可能无法获得这样的研究参与机会。参与者将接触到尖端的ML研究，以及专业发展活动，如技术研讨会和职业相关研讨会。此外，AMALTHEA的目标是在夏季体验期间让10名研究生参与本科教学和指导活动。最后，该项目的研究和教育工作得到了其顾问委员会的支持，该委员会由经验丰富的教育工作者、ML行业从业者和研究人员组成。研究结果将发表在跨学科会议上，并可能发表在技术期刊上。REU网站（http：www.amalthea-reu.org）为学生以及教育工作者和机器学习研究人员提供更多信息。

The Advances of MAchine Learning in THEory & Applications (AMALTHEA) REU Site aims to provide top quality educational experiences to a diverse community of undergraduate students through research participation in the area of Machine Learning (ML). The relevance and importance of ML is not limited to specialized technological innovations, as it was in the past. Nowadays, it also increasingly influences everyday life through its contributions to applications such as voice/face recognition, credit fraud detection, intelligent recommendation systems and many others. Furthermore, ML is inherently multi-disciplinary as it draws from advances in disciplines such as computing, statistics, mathematics, physics, biology and engineering, to a name a few major ones. The project's thrust area is the theory of ML and how it can be integrated and applied to important real-life problems, thus exposing participants to both theory and applications. AMALTHEA involves 10 undergraduate students per year from a broad spectrum of disciplines for 10 weeks in the summer. These participants perform supervised research, whose results are going to impact the field of ML itself, as well as how ML is applied in other scientific disciplines. For this purpose, the faculty mentors have ample expertise in ML and past experience of effectively engaging undergraduate students into state-of-the-art research.Over its lifespan, the project will directly impact a diverse group of 30 motivated students, the majority of which may not have access to such research participation opportunities otherwise. The participants will be exposed to cutting-edge ML research, as well as professional development activities, such as technical seminars and career-related workshops. Furthermore, AMALTHEA aims to involve overall 10 graduate students in undergraduate teaching and mentoring activities during the summer experiences. Finally, the project's research and education endeavors are supported by its advisory board, which consists of seasoned educators, ML industry practitioners and researchers. Research results will be published in interdisciplinary conferences, and, potentially, technical journals.The REU Site web site (http://www.amalthea-reu.org) provides additional information for students as well as educators and researchers in machine learning.