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

REU 网站：机器学习理论进展

• 批准号: 1560345
• 负责人: Georgios Anagnostopoulos
• 金额: $ 36万
• 依托单位: Florida Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-03-15 至 2020-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1560345&HistoricalAwards=false
• 关键词: REU; Site; Advances; Machine; Learning

The Advances of MAchine Learning in THEory and Applications (AMALTHEA) Research Experiences for Undergraduates (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 multiple disciplines such as engineering, computing, statistics, mathematics, physics and biology, to name a few major ones. Since its start in 2009, AMALTHEA, one of the first ML-focused REU sites, involves 10 undergraduate students per year from a broad spectrum of disciplines, and the educational experience spans 10 weeks in the summer. The participants are exposed to cutting-edge ML research, as well as professional development activities, such as technical seminars and career-related workshops. Moreover, these participants perform closely-mentored research, whose results are going to impact the field of ML itself, as well as how ML is applied in other scientific disciplines. Over the 2016-2019 time span, 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 project's thrust area is the theory of ML and how it can be integrated and applied to important real-life problems, hence exposing participants to both theory and applications. Past projects include applications such as automated anuran recognition from frog calls, uncovering criminal networks from crime locations, human-object interaction recognition, modelling of group dynamics in virtual worlds, speaker-independent speech recognition and license plate recognition among others. On the other hand, past contributions to the theory of ML have been steered towards topics such as functional data analysis, wavelet-based density estimation, non-linear dimensionality reduction, kernel methods and anomaly detection to name a few. Short video highlights of such projects can be found on AMALTHEA's YouTube channel located at https://goo.gl/2JhYoF. Finally, additional information about these topics and their outcomes can be found on the project's web site located at http://www.amalthea-reu.org.

机器学习理论与应用进展 (AMALTHEA) 本科生研究体验 (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。机器学习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，它还通过对语音/人脸识别、信用欺诈检测、智能推荐系统等应用的贡献，日益影响着日常生活。此外，机器学习本质上是多学科的，因为它借鉴了工程、计算、统计学、数学、物理和生物学等多个学科的进步。自 2009 年成立以来，AMALTHEA 是首批专注于 ML 的 REU 网站之一，每年招收 10 名来自各个学科的本科生，夏季的教育体验持续 10 周。参与者可以接触到前沿的机器学习研究以及专业发展活动，例如技术研讨会和职业相关研讨会。此外，这些参与者进行密切指导的研究，其结果将影响机器学习本身领域，以及机器学习在其他科学学科中的应用方式。在 2016 年至 2019 年期间，该项目将直接影响 30 名积极进取的学生组成的多元化群体，否则他们中的大多数人可能无法获得此类研究参与机会。该项目的主旨领域是机器学习理论及其如何实现整合并应用于重要的现实生活问题，从而使参与者接触到理论和应用。过去的项目包括诸如从青蛙叫声中自动识别无尾鸟、从犯罪地点揭露犯罪网络、人机交互识别、虚拟世界中的群体动态建模、独立于说话人的语音识别和车牌识别等应用。另一方面，过去对机器学习理论的贡献主要集中在函数数据分析、基于小波的密度估计、非线性降维、核方法和异常检测等主题。此类项目的短视频亮点可以在 AMALTHEA 的 YouTube 频道上找到，网址为：https://goo.gl/2JhYoF。最后，有关这些主题及其成果的更多信息可以在该项目的网站上找到：http://www.amalthea-reu.org。