Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Cheonbok Park"'
With deep learning (DL) outperforming conventional methods for different tasks, much effort has been devoted to utilizing DL in various domains. Researchers and developers in the traffic domain have also designed and improved DL models for forecastin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5650b202d204ae806b1be29e93292852
Publikováno v:
Advances in Knowledge Discovery and Data Mining ISBN: 9783031059322
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3a104dd5ddf0a93a15e7bade26c78446
https://doi.org/10.1007/978-3-031-05933-9_28
https://doi.org/10.1007/978-3-031-05933-9_28
Publikováno v:
ICDE
To tackle ever-increasing city traffic congestion problems, researchers have proposed deep learning models to aid decision-makers in the traffic control domain. Although the proposed models have been remarkably improved in recent years, there are sti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6074bfc0b412ad7b76dd9c81bc0d646f
http://arxiv.org/abs/2105.05504
http://arxiv.org/abs/2105.05504
Autor:
Sungahn Ko, Yunwon Tae, Cheonbok Park, Kihwan Kim, Hyojin Bahng, Jaegul Choo, Seungmin Jin, Chunggi Lee
Publikováno v:
CIKM
Predicting road traffic speed is a challenging task due to different types of roads, abrupt speed change and spatial dependencies between roads; it requires the modeling of dynamically changing spatial dependencies among roads and temporal patterns o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5c4226af12d43f30de8b7e383eac5219
https://doi.org/10.1145/3340531.3411940
https://doi.org/10.1145/3340531.3411940
Autor:
Lucy Park, Taehee Kim, Yunwon Tae, Mohammad Azam Khan, Cheonbok Park, Soyoung Yang, Jaegul Choo
Publikováno v:
ACL/IJCNLP (1)
Unsupervised machine translation, which utilizes unpaired monolingual corpora as training data, has achieved comparable performance against supervised machine translation. However, it still suffers from data-scarce domains. To address this issue, thi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b5215d756880d4322a51c34202e084d3
http://arxiv.org/abs/2010.09046
http://arxiv.org/abs/2010.09046
Publikováno v:
CHI
Document labeling is a critical step in building various machine learning applications. However, the step can be time-consuming and arduous, requiring a significant amount of human efforts. To support an efficient document labeling environment, we pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::63eae6672143d700d7ea6f835435cf69
https://doi.org/10.1145/3290605.3300460
https://doi.org/10.1145/3290605.3300460
Publikováno v:
Publons
Missing values cause critical problems on training a prediction model. Various missing data imputation methods have been introduced to settle down the problem. However, the imputation accuracy obtained by the methods is insufficient to validate perfo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1f46f00cdc823a9b59dfbec020b33df6
https://doi.org/10.23919/icact.2019.8702000
https://doi.org/10.23919/icact.2019.8702000