Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Ryota Higa"'
Autor:
Ryota Higa, Hiro Fujihara, Hiroyuki Toda, Masakazu Kobayashi, Kenichi Ebihara, Akihisa Takeuchi
Publikováno v:
Materials Transactions; 2024, Vol. 65 Issue 8, p899-906, 8p
Autor:
Hiroyuki Toda, Kyosuke Hirayama, Shogo Yamaguchi, Hiro Fujihara, Ryota Higa, Kazuyuki Shimizu, Akihisa Takeuchi, Masayuki Uesugi
Publikováno v:
Materials Transactions; 2023, Vol. 64 Issue 12, p2729-2738, 10p
Autor:
Ryota Higa, Shinji Nakadai
Publikováno v:
2022 IEEE 18th International Conference on Automation Science and Engineering (CASE).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fc95918026482348bd3dc9c16b651d08
https://doi.org/10.1109/case49997.2022.9926449
https://doi.org/10.1109/case49997.2022.9926449
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 36:13065-13066
Existing research in the field of automated negotiation considers a negotiation architecture in which some of the negotiation components are designed separately by reinforcement learning (RL), but comprehensive negotiation strategy design has not bee
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4185b9261ecb1acce12588ca072b3d1c
https://doi.org/10.1609/aaai.v36i11.21669
https://doi.org/10.1609/aaai.v36i11.21669
Publikováno v:
IEEE Access, Vol 12, Pp 58519-58531 (2024)
Deep neural networks (DNNs) have proven highly effective in various computational tasks, but their success depends largely on access to large datasets with accurate labels. Obtaining such data may be challenging and costly in real-world scenarios. Co
Externí odkaz:
https://doaj.org/article/aa2d6fc03a194480a46540accadfcdf2
Publikováno v:
IROS
This paper addresses the problem of path negotiation among self-interested multirobot operators in shared space. In conventional multirobot path planning problems, most of the research thus far has focused on the coordination and planning of collisio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1103304a219c34b0a3d35ae542919689
https://doi.org/10.1109/iros45743.2020.9341305
https://doi.org/10.1109/iros45743.2020.9341305
Publikováno v:
Applied Sciences, Vol 14, Iss 3, p 1208 (2024)
This paper addresses the performance degradation of deep neural networks caused by learning with noisy labels. Recent research on this topic has exploited the memorization effect: networks fit data with clean labels during the early stages of learnin
Externí odkaz:
https://doaj.org/article/eb842868c4534db9a1fe829bcbf67088
Autor:
Ryota Higa, Kenichi Asano
Publikováno v:
Physical Review B. 93
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2d240e0ada365d244d92f2d9a3c685c2
https://doi.org/10.1103/physrevb.93.245123
https://doi.org/10.1103/physrevb.93.245123
Publikováno v:
Journal of Bioresources and Bioproducts, Vol 7, Iss 1, Pp 33-42 (2022)
Brønsted acid site (S/Cl)-functional carbon materials were prepared by ball-milling (bm) L-cysteine and ammonium chloride to form chemical complex solids, by post-heat treatment (Q) of the solids at 500 °C under a nitrogen gas atmosphere to stabili
Externí odkaz:
https://doaj.org/article/b9ac45af6aec4c088907c220a6d60d5b
Publikováno v:
Journal of the Optical Society of America B. 29:2691
A surface magnon-polariton can be excited by both p- and s-polarized light if at least one of the layers is a magnetic material. We present general expressions of the tangential wave vectors of s- and p-polarized light at an interface of two media. A
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::be3557727c0be5d4446fa74fe60bee40
https://doi.org/10.1364/josab.29.002691
https://doi.org/10.1364/josab.29.002691