Zobrazeno 1 - 10
of 7 553
pro vyhledávání: '"Wang, I."'
Autor:
Hsu, Chia-Yu, Wang, I-Hsiang
Reliability of sequential hypothesis testing can be greatly improved when decision maker is given the freedom to adaptively take an action that determines the distribution of the current collected sample. Such advantage of sampling adaptivity has bee
Externí odkaz:
http://arxiv.org/abs/2405.06554
Autor:
Li, Ching-Fang, Wang, I-Hsiang
In hypothesis testing problems, taking samples sequentially and stopping opportunistically to make the inference greatly enhances the reliability. The design of the stopping and inference policy, however, critically relies on the knowledge of the und
Externí odkaz:
http://arxiv.org/abs/2401.16213
Autor:
Johnson, Erik C., Robinson, Brian S., Vallabha, Gautam K., Joyce, Justin, Matelsky, Jordan K., Norman-Tenazas, Raphael, Western, Isaac, Villafañe-Delgado, Marisel, Cervantes, Martha, Robinette, Michael S., Reddy, Arun V., Kitchell, Lindsey, Rivlin, Patricia K., Reilly, Elizabeth P., Drenkow, Nathan, Roos, Matthew J., Wang, I-Jeng, Wester, Brock A., Gray-Roncal, William R., Hoffmann, Joan A.
Despite the progress in deep learning networks, efficient learning at the edge (enabling adaptable, low-complexity machine learning solutions) remains a critical need for defense and commercial applications. We envision a pipeline to utilize large ne
Externí odkaz:
http://arxiv.org/abs/2305.17300
Autor:
Wang, Yu Guo, Wang, I Ta
Publikováno v:
Education + Training, 2024, Vol. 66, Issue 1, pp. 35-53.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/ET-05-2023-0171
Autor:
Finocchio, Giovanni, Incorvia, Jean Anne C., Friedman, Joseph S., Yang, Qu, Giordano, Anna, Grollier, Julie, Yang, Hyunsoo, Ciubotaru, Florin, Chumak, Andrii, Naeemi, Azad J., Cotofana, Sorin D., Tomasello, Riccardo, Panagopoulos, Christos, Carpentieri, Mario, Lin, Peng, Pan, Gang, Yang, J. Joshua, Todri-Sanial, Aida, Boschetto, Gabriele, Makasheva, Kremena, Sangwan, Vinod K., Trivedi, Amit Ranjan, Hersam, Mark C., Camsari, Kerem Y., McMahon, Peter L., Datta, Supriyo, Koiller, Belita, Aguilar, Gabriel H., Temporão, Guilherme P., Rodrigues, Davi R., Sunada, Satoshi, Everschor-Sitte, Karin, Tatsumura, Kosuke, Goto, Hayato, Puliafito, Vito, Åkerman, Johan, Takesue, Hiroki, Di Ventra, Massimiliano, Pershin, Yuriy V., Mukhopadhyay, Saibal, Roy, Kaushik, Wang, I-Ting, Kang, Wang, Zhu, Yao, Kaushik, Brajesh Kumar, Hasler, Jennifer, Ganguly, Samiran, Ghosh, Avik W., Levy, William, Roychowdhury, Vwani, Bandyopadhyay, Supriyo
Publikováno v:
Nano Futures (2024)
In the "Beyond Moore's Law" era, with increasing edge intelligence, domain-specific computing embracing unconventional approaches will become increasingly prevalent. At the same time, adopting a variety of nanotechnologies will offer benefits in ener
Externí odkaz:
http://arxiv.org/abs/2301.06727
Standard deep reinforcement learning (DRL) aims to maximize expected reward, considering collected experiences equally in formulating a policy. This differs from human decision-making, where gains and losses are valued differently and outlying outcom
Externí odkaz:
http://arxiv.org/abs/2208.09106
Publikováno v:
Harmonia: Journal of Arts Research and Education, Vol 23, Iss 2, Pp 223-234 (2023)
Although the Flow experience has been researched extensively in music education, there is limited investigation into exploring the link between the Suzuki piano method and Csikszentmihalyi’s flow theory. To address this gap, a quasi-experimental st
Externí odkaz:
https://doaj.org/article/bf5ac7b8692e45819c2805be99f2464d
Autor:
Wang, I-Kuan1,2 (AUTHOR), Chan, Chan Ip3,4 (AUTHOR), Lin, Alfred Hsing-Fen5 (AUTHOR), Yu, Tung-Min2,6 (AUTHOR), Yen, Tzung-Hai7,8 (AUTHOR), Lai, Ping-Chin1 (AUTHOR), Li, Chi-Yuan2,9 (AUTHOR), Sung, Fung-Chang10,11,12 (AUTHOR) fcsung1008@yahoo.com
Publikováno v:
PLoS ONE. 3/29/2024, Vol. 19 Issue 3, p1-12. 12p.
Autor:
Chang, Hsiang-Yu1,2,3 (AUTHOR), Wang, I-Fan1,2 (AUTHOR) ifanwang.gbs@gmail.com
Publikováno v:
Scientific Reports. 2/26/2024, Vol. 14 Issue 1, p1-9. 9p.
Publikováno v:
In International Journal of Heat and Mass Transfer October 2024 231