Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Ho-Taek Joo"'
Autor:
Yunho Choi, Songmi Oh, Jin Won Huh, Ho-Taek Joo, Hosu Lee, Wonsang You, Cheng-mok Bae, Jae-Hun Choi, Kyung-Joong Kim
Publikováno v:
Communications Medicine, Vol 4, Iss 1, Pp 1-11 (2024)
Abstract Background Sepsis is one of the most life-threatening medical conditions. Therefore, many clinical trials have been conducted to identify optimal treatment strategies for sepsis. However, finding reliable strategies remains challenging due t
Externí odkaz:
https://doaj.org/article/0db20e33c309483ab2b424151d419ef0
Publikováno v:
IEEE Access, Vol 10, Pp 57369-57382 (2022)
Offline reinforcement learning (RL) is applied to fixed datasets of logged interactions pertaining to actual applications in healthcare, autonomous vehicles, and robotics. In limited and fixed dataset settings, data augmentation can be beneficial in
Externí odkaz:
https://doaj.org/article/63d4ca3c14204659957acaebb1390161
Publikováno v:
Expert Systems with Applications. 213:118979
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::00a997dd4ce9f7d4688bbecbca2d6aea
https://doi.org/10.1016/j.eswa.2022.118979
https://doi.org/10.1016/j.eswa.2022.118979
Autor:
Kyung-Joong Kim, Ho-Taek Joo
Publikováno v:
AAAI
Humans are usually good at guessing whether the two games are similar to each other and easily estimate how much time to master new games based on the similarity. Although Deep Reinforcement Learning (DRL) has been successful in various domains, it t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1c6e36df4240cf88c062954cb06a8bfb
https://doi.org/10.1609/aaai.v34i10.7188
https://doi.org/10.1609/aaai.v34i10.7188
Autor:
Ho-Taek Joo, Kyung-Joong Kim
Publikováno v:
CoG
Deep Reinforcement Learning (DRL) allows agents to learn strategies to solve complex tasks. It has been applied to solve various problems such as natural language processing, games, etc. However, it is still difficult to apply DRL to certain real-wor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b339cb777a21ecf09637ea7504a65092
https://doi.org/10.1109/cig.2019.8847950
https://doi.org/10.1109/cig.2019.8847950
Autor:
Hickling, Thomas1 (AUTHOR) tom.hickling@city.ac.uk, Zenati, Abdelhafid1 (AUTHOR) abdelhafid.zenati@city.ac.uk, Aouf, Nabil1 (AUTHOR) nabil.aouf@city.ac.uk, Spencer, Phillippa2 (AUTHOR) PSpencer@mail.dstl.gov.uk
Publikováno v:
ACM Computing Surveys. May2024, Vol. 56 Issue 5, p1-35. 35p.
Publikováno v:
ACM Transactions on Multimedia Computing, Communications & Applications; Jul2024, Vol. 20 Issue 7, p1-20, 20p
Autor:
Amina Adadi, Afaf Bouhoute
Artificial Intelligence (AI) and Machine Learning (ML) are set to revolutionize all industries, and the Intelligent Transportation Systems (ITS) field is no exception. While ML, especially deep learning models, achieve great performance in terms of a
