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.

该提案旨在增加对计算机科学研究和高级研究职业感兴趣的美国公民和永久居民本科生的数量。理论和实证机器学习培训将使参与者能够以创新方式为最高水平的无处不在的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、女性和代表性不足的少数族裔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富有成效的研究人员。计算机视觉通过人脸识别和自动驾驶汽车等应用，对国家安全和交通的未来产生深远的影响。自然语言处理，通过高效的大量语义分析和来自不同来源的文本文档的总结等应用，除了工业界可以利用的许多其他可能性之外，还对国家安全产生影响。该提案的目的是让那些聪明、积极进取、希望在计算机科学领域从事高级职业的本科生在职业生涯早期获得积极的研究经验。该提案旨在开发一个 REU 网站，通过接触大学研究中提供的机会来拓宽参与者的知识视野。学生将参与机器学习技术和利用机器学习的新兴应用程序的研究项目。感兴趣的应用是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结合理论阅读、分析和研究。将向学生介绍这些主题，并通过介绍性演示帮助他们深入了解所选主题。然后，他们将对新问题进行实践研究，进行实验，并通过书面论文和演示文稿传达他们的结果。 REU 的学生将在大学环境中与教师导师和研究生一起参与机器学习及其在各种新兴领域的应用研究。该研究将让本科生参与前沿研究，他们将编写软件来解决有趣且及时的问题，并撰写论文发表。

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）

ParallelAttentionMechanismsinNeuralMachine Translation

神经机器翻译中的并行注意机制

DOI：
发表时间：
2018-12
期刊：
International Conference on Machine Learning Applications
影响因子：
0
作者：
Medina, Julian;Kalita, Jugal
通讯作者：
Kalita, Jugal

Unsupervised Learning of Depth and Ego-Motion From Cylindrical Panoramic Video

圆柱形全景视频的深度和自我运动的无监督学习

DOI：
10.1109/aivr46125.2019.00018
发表时间：
2019-12
期刊：
2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR
影响因子：
0
作者：
Sharma, Alisha;Ventura, Jonathan
通讯作者：
Ventura, Jonathan

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

使用辅助损失函数和自定义评估指标改进计算机生成的对话

DOI：
10.1016/j.neucom.2021.08.151
发表时间：
2021-06-04
期刊：
Neurocomputing
影响因子：
6
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：
2018-04-20
期刊：
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
影响因子：
0
作者：
Diptodip Deb;Jonathan Ventura
通讯作者：
Jonathan Ventura

Open Set Text Classification using Convolutional Neural Networks

使用卷积神经网络进行开放集文本分类