TY - GEN
T1 - A Survey of Missing Data Imputation Using Generative Adversarial Networks
AU - Kim, Jaeyoon
AU - Tae, Donghyun
AU - Seok, Junhee
N1 - Funding Information:
The correspondence should be addressed to jseok14@korea.ac.kr. This work was supported by grants from the National Research Foundation of Korea (NRF-2017R1C1B2002850, NRF-2019R1A2C1084778)
Publisher Copyright:
© 2020 IEEE.
PY - 2020/2/1
Y1 - 2020/2/1
N2 - Recently, many deep learning models for missing data imputation have been studied. One of the most popular models is Generative Adversarial Networks (GANs), which generate plausible fake data through adversarial training. In this paper, we take a look at the architecture, objective of a generator and a discriminator, training method and loss function. After that, we can see what improvements have been made to each model. Moreover, we can easily compare several GAN-based models for missing data imputation.
AB - Recently, many deep learning models for missing data imputation have been studied. One of the most popular models is Generative Adversarial Networks (GANs), which generate plausible fake data through adversarial training. In this paper, we take a look at the architecture, objective of a generator and a discriminator, training method and loss function. After that, we can see what improvements have been made to each model. Moreover, we can easily compare several GAN-based models for missing data imputation.
KW - Adversarial training
KW - Discriminator
KW - Generative Adversarial Networks (GANs)
KW - Generator
KW - Missing data imputation
UR - http://www.scopus.com/inward/record.url?scp=85084035336&partnerID=8YFLogxK
U2 - 10.1109/ICAIIC48513.2020.9065044
DO - 10.1109/ICAIIC48513.2020.9065044
M3 - Conference contribution
AN - SCOPUS:85084035336
T3 - 2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020
SP - 454
EP - 456
BT - 2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020
Y2 - 19 February 2020 through 21 February 2020
ER -