Zobrazeno 1 - 10
of 54
pro vyhledávání: '"Young-Sung Son"'
Publikováno v:
IEEE Access, Vol 8, Pp 146588-146597 (2020)
Deep reinforcement learning (DRL) is a promising approach for developing control policies by learning how to perform tasks. Edge devices are required to control their actions by exploiting DRL to solve tasks autonomously in various applications such
Externí odkaz:
https://doaj.org/article/5613f6ff2a2946caa76f8406e029b013
Autor:
Qihan Yang, Somesh Kumar, Qiaoyong Zhong, Fan Feng, Liang Ma, Qi She, Siew-Kei Lam, Gabriele Graffieti, German Ignacio Parisi, Yangsheng Xu, Baoquan Chen, Tin Lun Lam, Eoin Brophy, Chuanlin Lan, Vidit Goel, Lin Yang, Qi Liu, Rosa H. M. Chan, Debdoot Sheet, Shiliang Pu, Di Xie, Lorenzo Pellegrini, Hyonyoung Han, Liguang Zhou, Vincenzo Lomonaco, Zhengwei Wang, Soonyong Song, Davide Maltoni, Heechul Bae, Jianwen Wu, Xinyue Hao, Tomas E. Ward, Duvindu Piyasena, Sathursan Kanagarajah, Meiqing Wu, Young-Sung Son
Publikováno v:
IEEE Robotics & Automation Magazine. 27:11-16
Humans have a remarkable ability to learn continuously from th e environment and inner experience. One of the grand goals of robots is to build an artificial "lifelong learning" agent that can shape a cultivated understanding of the world from the cu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::26ea5e8210ef6c78f2ba2436e0e0d4c1
https://doi.org/10.1109/mra.2020.2987186
https://doi.org/10.1109/mra.2020.2987186
Publikováno v:
IEEE Access, Vol 8, Pp 146588-146597 (2020)
Deep reinforcement learning (DRL) is a promising approach for developing control policies by learning how to perform tasks. Edge devices are required to control their actions by exploiting DRL to solve tasks autonomously in various applications such
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8c74bf1ab2ed63a2f374145ab82039ed
https://doi.org/10.1109/access.2020.3014922
https://doi.org/10.1109/access.2020.3014922
Publikováno v:
ICTC
Robot learning by demonstration is a research paradigm that can play an important role in expanding areas where robots can be applied. An easy method to get a policy to reproduce the demonstrated behavior is to learn a model that maps directly from d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dffff8122e954fbfded1197abeb22f77
https://doi.org/10.1109/ictc49870.2020.9289148
https://doi.org/10.1109/ictc49870.2020.9289148
Publikováno v:
ICTC
Applying deep learning to symbolic planning is not straightforward because they differently internalize knowledge. One represents knowledge numerically while the other does symbolically. Hybrid methods that take strengths from both techniques will de
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0e4c29bf1571c0c50373c7c1942c0069
https://doi.org/10.1109/ictc49870.2020.9289296
https://doi.org/10.1109/ictc49870.2020.9289296
Publikováno v:
ICTC
In this paper, we proposed acoustic signal visualization for flying drone classifications and provided performance benchmarks for backbone deep neural networks. To visualize acoustic signals, we transformed the signals to 3-channel images by spectrog
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0b256b962daa20a1dcd93855dd9f294d
https://doi.org/10.1109/ictc49870.2020.9289516
https://doi.org/10.1109/ictc49870.2020.9289516
Autor:
Son Jongkwon, Young-Sung Son
Publikováno v:
ICTC
The people who spend most of their time indoors are always threatened by indoor air pollutants. To protect the health of individuals from these threats, the government tried to provide sufficient attention and management of pollutants based on the re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1174ef27505bc22b95b74d90e0d37ae6
https://doi.org/10.1109/ictc46691.2019.8939605
https://doi.org/10.1109/ictc46691.2019.8939605
Publikováno v:
ICTC
In area of the reinforcement learning, an environment is important because when a well-known reinforcement learning technique for an environment is applied to another environment, it does not guarantee whether the technique also works well or not. To
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eaed2acce8ad569696d0c6abf17a6cde
https://doi.org/10.1109/ictc46691.2019.8939754
https://doi.org/10.1109/ictc46691.2019.8939754
Autor:
Sooyoung Jang, Young-Sung Son
Publikováno v:
ICTC
Hyperparameter optimization has a considerable impact on system performance. However many researchers use the default hyperparameter configurations provided by the machine learning frameworks they use because it require a lot of effort, time and comp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::11730dfb66f14015274621c730e8655c
https://doi.org/10.1109/ictc46691.2019.8939854
https://doi.org/10.1109/ictc46691.2019.8939854
Autor:
Sooyoung Jang, Young-Sung Son
Publikováno v:
MobiSys
The virtual world is essential for deep reinforcement learning. Since the deep reinforcement learning agent learns the optimal policy by interacting with the environment in a trial and error manner, training the agent in the real world is not only co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c407e39ac9b558c3657943cba4219083
https://doi.org/10.1145/3307334.3328602
https://doi.org/10.1145/3307334.3328602