Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Yasuyuki Okoshi"'
Autor:
Junnosuke Suzuki, Jaehoon Yu, Mari Yasunaga, Angel Lopez Garcia-Arias, Yasuyuki Okoshi, Shungo Kumazawa, Kota Ando, Kazushi Kawamura, Thiem Van Chu, Masato Motomura
Publikováno v:
IEEE Access, Vol 12, Pp 2057-2073 (2024)
With the widespread adoption of edge AI, the diversity of application requirements and fluctuating computational demands present significant challenges. Conventional accelerators suffer from increased memory footprints due to the need for multiple mo
Externí odkaz:
https://doaj.org/article/d7aa8884e28346a9bcfad7530e418021
Publikováno v:
IEEE Access, Vol 11, Pp 16588-16604 (2023)
Accurate neural networks can be found just by pruning a randomly initialized overparameterized model, leaving out the need for any weight optimization. The resulting subnetworks are small, sparse, and ternary, making excellent candidates for efficien
Externí odkaz:
https://doaj.org/article/0817fb22196e41d682ca86606a1bb546
Autor:
Kazutoshi Hirose, Jaehoon Yu, Kota Ando, Yasuyuki Okoshi, Angel Lopez Garcia-Arias, Junnosuke Suzuki, Thiem Van Chu, Kazushi Kawamura, Masato Motomura
Publikováno v:
2022 IEEE International Solid- State Circuits Conference (ISSCC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::55a4eb26dbd18507e39a3ba58245b64a
https://doi.org/10.1109/isscc42614.2022.9731668
https://doi.org/10.1109/isscc42614.2022.9731668