Undergraduate Research and Education in Quantum Machine Learning

被引：2

作者：

Uehara, Glen ^{[1
]}

Larson, Jean ^{[2
]}

Barnard, Wendy ^{[3
]}

Esposito, Michael ^{[4
]}

Posta, Filippo ^{[5
]}

Yarter, Maxwell ^{[1
]}

Sharma, Aradhita ^{[1
]}

Kyriacou, Niki ^{[6
]}

Dobson, Matthew ^{[1
]}

Spanias, Andreas ^{[1
]}

机构：

[1] ASU, SenSIP Ctr, ECEE, Tempe, AZ 85281 USA

[2] ASU, CBBG, SEBE, Tempe, AZ USA

[3] ASU, CREST, Tempe, AZ USA

[4] ASU, SenSIP Ctr, SOLS, Tempe, AZ USA

[5] EMCC, Math, Brussels, Belgium

[6] ASU, SenSIP Ctr, Phys, Tempe, AZ USA

来源：

2022 IEEE FRONTIERS IN EDUCATION CONFERENCE, FIE | 2022年

关键词：

quantum computing; machine learning; AI; quantum audio and image processing;

D O I：

10.1109/FIE56618.2022.9962749

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This Work-In-Progress paper describes a program in quantum machine learning launched in the academic year of 2021-22. The program engaged undergraduate students from STEM areas with faculty and industry mentors. Because of the COVID-19 conditions, this undergraduate engagement was offered in a virtual format. In 2022, some face-to-face meetings with presentations were also held. The program included: a) training in machine learning with quantum simulators, b) weekly presentations, and c) semester end presentations. The assessment of the program included surveys, interviews, and presentation observations. Challenges and opportunities from virtual engagement were also part of the assessment.

引用

页数：5

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