REU Site: Machine Learning in Natural Language Processing and Computer Vision

REU 网站：自然语言处理和计算机视觉中的机器学习

基本信息

批准号：
1659788
负责人：
Jugal Kalita
金额：
$ 37.99万
依托单位：
University of Colorado at Colorado Springs
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-06-01 至 2020-05-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1659788&HistoricalAwards=false
关键词：
REU Site Machine Learning Natural

项目摘要

The proposal seeks to increase the number of American citizens and permanent resident undergraduates who are attracted to careers in research and advanced studies in Computer Science. Training in theoretical and empirical machine learning will enable participants to contribute to ubiquitous software-based technologies at the highest levels in innovative ways. The proposal will also focus almost exclusively on training future computer scientists from institutions with limited research opportunities, women and under-represented minorities. The research experience will encourage these students to be productive researchers in academic and non-academic environments during their future careers. Computer vision, through applications such as face recognition and autonomous vehicles, has profound implications for society in terms of future of national security and transportation. Natural language processing, through applications such as efficient large volume semantic analysis and summarization of textual documents from disparate sources, also has implications for national security in addition to numerous other possibilities that can be exploited by industry. The objective of this proposal is to expose bright and motivated undergraduates who want to pursue advanced careers in Computer Science to active research experience early in their careers. This proposal seeks to develop an REU site to broaden the intellectual horizon of participants through exposure to opportunities available in university research. Students will be involved in research projects in machine learning techniques and in emerging applications that exploit machine learning. The applications of interest are in the fields of natural language processing and computer vision. Students will have the opportunity to utilize a combination of theoretical reading, analysis, and research within laboratory environments. The students will be introduced to the topics and helped to obtain in-depth understanding of selected topics through introductory presentations. Then, they will perform hands-on research on novel problems, conduct experiments, and communicate their results through written papers and presentations. The REU students will be involved in research in machine learning and its applications in diverse and emergent areas alongside faculty mentors and graduate students in a university environment. The research will involve undergraduate students in cutting-edge research where they will write software to solve interesting and timely problems and write papers for publication.

该提案旨在增加受到计算机科学研究和高级研究职业的吸引的美国公民和永久居民本科生的数量。理论和经验机器学习中的培训将使参与者能够以创新的方式以最高级别的无处,、基于软件的技术做出贡献。该提案还将几乎完全专注于培训来自研究机会有限的机构，妇女和代表性不足的少数民族的未来计算机科学家。研究经验将鼓励这些学生在未来的职业生涯中成为学术和非学术环境中的生产研究人员。通过诸如面部识别和自动驾驶汽车之类的应用，计算机视觉对社会在国家安全和运输的未来方面具有深远的影响。自然语言处理，通过有效的大量语义分析和来自不同来源的文本文档的汇总，除了行业可以利用的许多其他可能性外，还对国家安全也有影响。该提案的目的是揭露希望从事计算机科学领域的高级职业的光明而有动力的大学生，以便在职业生涯的早期积极研究经验。该建议旨在开发一个REU站点，以通过接触大学研究的机会来扩大参与者的智力视野。学生将参与机器学习技术的研究项目以及利用机器学习的新兴应用程序。感兴趣的应用在自然语言处理和计算机视觉领域。学生将有机会在实验室环境中利用理论阅读，分析和研究的结合。将向学生介绍主题，并通过介绍性演讲有助于深入了解选定的主题。然后，他们将对新型问题，进行实验进行动手研究，并通过书面论文和演讲来传达其结果。 REU的学生将与大学环境中的教师导师和研究生一起参与机器学习及其在各种和新兴地区的应用。这项研究将涉及本科生参与尖端研究，他们将编写软件来解决有趣，及时的问题并撰写论文以发表。

项目成果

期刊论文数量（11）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Improving Computer Generated Dialog with Auxiliary Loss Functions and Custom Evaluation Metrics

DOI：
发表时间：
2021-06
期刊：
影响因子：
0
作者：
T. Conley
通讯作者：
T. Conley

An Aggregated Multicolumn Dilated Convolution Network for Perspective-Free Counting

DOI：
10.1109/cvprw.2018.00057
发表时间：
2018-01-01
期刊：
PROCEEDINGS 2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW)
影响因子：
0
作者：
Deb, Diptodip;Ventura, Jonathan
通讯作者：
Ventura, Jonathan

Isolated and Ensemble Audio Preprocessing Methods for Detecting Adversarial Examples against Automatic Speech Recognition

用于检测自动语音识别的对抗性示例的隔离和集成音频预处理方法