no code implementations • 6 Apr 2024 • Azaan Rehman, Alexander Zhovmer, Ryo Sato, Yosuke Mukoyama, Jiji Chen, Alberto Rissone, Rosa Puertollano, Harshad Vishwasrao, Hari Shroff, Christian A. Combs, Hui Xue
Previous methods are based on convolutional neural networks (CNNs) which generally require more time-consuming training of separate models for each new imaging experiment, impairing the applicability and generalization.
no code implementations • 26 Nov 2023 • Arisa Ema, Ryo Sato, Tomoharu Hase, Masafumi Nakano, Shinji Kamimura, Hiromu Kitamura
This policy recommendation summarizes the issues related to the auditing of AI services and systems and presents three recommendations for promoting AI auditing that contribute to sound AI governance.
no code implementations • NeurIPS 2021 • Ryo Sato, Mirai Tanaka, Akiko Takeda
Although application examples of multilevel optimization have already been discussed since the 1990s, the development of solution methods was almost limited to bilevel cases due to the difficulty of the problem.