Data Cleansing for Deep Neural Networks with Storage-efficient Approximation of Influence Functions

1 code implementation • 22 Mar 2021 • Kenji Suzuki, Yoshiyuki Kobayashi, Takuya Narihira

Moreover, our simple and general proposed method to calculate influence scores is available on our auto ML tool without programing, Neural Network Console.

Neural Network Libraries: A Deep Learning Framework Designed from Engineers' Perspectives

1 code implementation • 12 Feb 2021 • Takuya Narihira, Javier Alonsogarcia, Fabien Cardinaux, Akio Hayakawa, Masato Ishii, Kazunori Iwaki, Thomas Kemp, Yoshiyuki Kobayashi, Lukas Mauch, Akira Nakamura, Yukio Obuchi, Andrew Shin, Kenji Suzuki, Stephen Tiedmann, Stefan Uhlich, Takuya Yashima, Kazuki Yoshiyama

While there exist a plethora of deep learning tools and frameworks, the fast-growing complexity of the field brings new demands and challenges, such as more flexible network design, speedy computation on distributed setting, and compatibility between different tools.

Autonomous Sub-domain Modeling for Dialogue Policy with Hierarchical Deep Reinforcement Learning

no code implementations • WS 2018 • Giovanni Yoko Kristianto, Huiwen Zhang, Bin Tong, Makoto Iwayama, Yoshiyuki Kobayashi

Solving composites tasks, which consist of several inherent sub-tasks, remains a challenge in the research area of dialogue.

Hierarchical Reinforcement Learning reinforcement-learning +1