Zobrazeno 1 - 10
of 196
pro vyhledávání: '"Tsan-Sheng Hsu"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-19 (2024)
Abstract A Go endgame database consists of optimal game values and moves for every legal arrangement of no more than S pieces on an N by N board. This paper describes methods for constructing such databases when $$1 < N \le 5$$ 1 < N ≤ 5 and $$S =
Externí odkaz:
https://doaj.org/article/d7bd2756f38c4ac3972549419e98f82d
Publikováno v:
IEEE Access, Vol 11, Pp 18157-18182 (2023)
The AlphaZero algorithm achieved superhuman levels of play in chess, shogi, and Go by learning without domain-specific knowledge except for game rules. This paper targets stochastic games and investigates whether AlphaZero can learn theoretical value
Externí odkaz:
https://doaj.org/article/c193262045494c36be6111ffd6a24b4e
Autor:
Meng-Tsung Tsai, Tsurng-Chen Chern, Jen-Hsiang Chuang, Chih-Wen Hsueh, Hsu-Sung Kuo, Churn-Jung Liau, Steven Riley, Bing-Jie Shen, Chih-Hao Shen, Da-Wei Wang, Tsan-Sheng Hsu
Publikováno v:
PLoS ONE, Vol 5, Iss 11, p e13292 (2010)
Early data from the 2009 H1N1 pandemic (H1N1pdm) suggest that previous studies over-estimated the within-country rate of spatial spread of pandemic influenza. As large spatially resolved data sets are constructed, the need for efficient simulation co
Externí odkaz:
https://doaj.org/article/3ebd70d7c99d4b20a8777e6606e72fba
Autor:
Tsan-Sheng Hsu, 徐贊昇
102
In this thesis, the problem for minimizing the power in the heterogeneous networks is considered. Heterogeneous networks is the mix of Macro base stations (BS) and some low power nodes. We consider Pico BS as low-power nodes. The major probl
In this thesis, the problem for minimizing the power in the heterogeneous networks is considered. Heterogeneous networks is the mix of Macro base stations (BS) and some low power nodes. We consider Pico BS as low-power nodes. The major probl
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/90431035948215929925
Publikováno v:
2022 International Conference on Technologies and Applications of Artificial Intelligence (TAAI).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad8a10fc3b193973bb3999071755bc87
https://doi.org/10.1109/taai57707.2022.00016
https://doi.org/10.1109/taai57707.2022.00016
Autor:
Tseng-Yi Chen, Chih Hsuan Chen, Hsin Wen Wei, Yu Pei Liang, Wei-Kuan Shih, Tsan-sheng Hsu, Shuo-Han Chen
Publikováno v:
Future Generation Computer Systems. 116:333-348
In the big data era, retaining the capability to process and store the sheer amount of data has become a necessity for data-intensive computing. To meet the requirement of big data processing, the storage-centric computing concept of processing data
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::643797ec368d8e6cb31febac94d6f517
https://doi.org/10.1016/j.future.2020.10.032
https://doi.org/10.1016/j.future.2020.10.032
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031114878
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a0abebaa2edc60b1e3b5214d60e99d48
https://doi.org/10.1007/978-3-031-11488-5_16
https://doi.org/10.1007/978-3-031-11488-5_16
Autor:
Wei Goh, Shu-Chen Tsai, Hung-Jui Chang, Ting-Yu Lin, Chien-Chi Chang, Mei-Lien Pan, Da-Wei Wang, Tsan-Sheng Hsu
Publikováno v:
Proceedings of the 12th International Conference on Simulation and Modeling Methodologies, Technologies and Applications.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6de3be88fe789c8ed9501ef78fd4de46
https://doi.org/10.5220/0011270100003274
https://doi.org/10.5220/0011270100003274
Publikováno v:
Proceedings of the 11th International Conference on Data Science, Technology and Applications.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dcf78dc881f7a61a7d021873ef47c84b
https://doi.org/10.5220/0011279100003269
https://doi.org/10.5220/0011279100003269
Autor:
Tsan-sheng Hsu, Shuo-Han Chen, Yu-Pei Liang, Tseng-Yi Chen, Wei-Kuan Shih, Yung-Han Hsu, Hsin-Wen Wei
Publikováno v:
DAC
Random forest has been widely used to classifying objects recently because of its efficiency and accuracy. On the other hand, nonvolatile memory has been regarded as a promising candidate to be a part of a hybrid memory architecture. For achieving th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fd6a96ef000b30cc2fa37e8833c90244
https://doi.org/10.1109/dac18074.2021.9586164
https://doi.org/10.1109/dac18074.2021.9586164