Yuka Hashimoto

According to our database, Yuka Hashimoto authored at least 18 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Quantum Circuit C^*-algebra Net.

Yuka Hashimoto, Ryuichiro Hataya

CoRR, 2024

Koopman operators with intrinsic observables in rigged reproducing kernel Hilbert spaces.

Isao Ishikawa, Yuka Hashimoto, Masahiro Ikeda, Yoshinobu Kawahara

CoRR, 2024

C^*-Algebraic Machine Learning: Moving in a New Direction.

Yuka Hashimoto, Masahiro Ikeda, Hachem Kadri

CoRR, 2024

2023

Deep Ridgelet Transform: Voice with Koopman Operator Proves Universality of Formal Deep Networks.

Sho Sonoda, Yuka Hashimoto, Isao Ishikawa, Masahiro Ikeda

CoRR, 2023

Koopman-Based Bound for Generalization: New Aspect of Neural Networks Regarding Nonlinear Noise Filtering.

Yuka Hashimoto, Sho Sonoda, Isao Ishikawa, Atsushi Nitanda, Taiji Suzuki

CoRR, 2023

Noncommutative C^*-algebra Net: Learning Neural Networks with Powerful Product Structure in C^*-algebra.

Ryuichiro Hataya, Yuka Hashimoto

CoRR, 2023

Deep learning with kernels through RKHM and the Perron-Frobenius operator.

Yuka Hashimoto, Masahiro Ikeda, Hachem Kadri

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning in RKHM: a C*-Algebraic Twist for Kernel Machines.

Yuka Hashimoto, Masahiro Ikeda, Hachem Kadri

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

A preconditioning technique for Krylov subspace methods in RKHSs.

Yuka Hashimoto, Takashi Nodera

J. Comput. Appl. Math., 2022

Learning in RKHM: a C^*-Algebraic Twist for Kernel Machines.

Yuka Hashimoto, Masahiro Ikeda, Hachem Kadri

CoRR, 2022

C^*-algebra Net: A New Approach Generalizing Neural Network Parameters to C^*-algebra.

Yuka Hashimoto, Zhao Wang, Tomoko Matsui

CoRR, 2022

C*-algebra Net: A New Approach Generalizing Neural Network Parameters to C*-algebra.

Yuka Hashimoto, Zhao Wang, Tomoko Matsui

Proceedings of the International Conference on Machine Learning, 2022

2021

Reproducing kernel Hilbert C*-module and kernel mean embeddings.

Yuka Hashimoto, Isao Ishikawa, Masahiro Ikeda, Fuyuta Komura, Takeshi Katsura, Yoshinobu Kawahara

J. Mach. Learn. Res., 2021

2020

Krylov Subspace Method for Nonlinear Dynamical Systems with Random Noise.

Yuka Hashimoto, Isao Ishikawa, Masahiro Ikeda, Yoichi Matsuo, Yoshinobu Kawahara

J. Mach. Learn. Res., 2020

Kernel Mean Embeddings of Von Neumann-Algebra-Valued Measures.

Yuka Hashimoto, Isao Ishikawa, Masahiro Ikeda, Fuyuta Komura, Yoshinobu Kawahara

CoRR, 2020

Analysis via Orthonormal Systems in Reproducing Kernel Hilbert C^*-Modules and Applications.

Yuka Hashimoto, Isao Ishikawa, Masahiro Ikeda, Fuyuta Komura, Takeshi Katsura, Yoshinobu Kawahara

CoRR, 2020

2018

Metric on Nonlinear Dynamical Systems with Koopman Operators.

Isao Ishikawa, Keisuke Fujii, Masahiro Ikeda, Yuka Hashimoto, Yoshinobu Kawahara

CoRR, 2018

Metric on Nonlinear Dynamical Systems with Perron-Frobenius Operators.

Isao Ishikawa, Keisuke Fujii, Masahiro Ikeda, Yuka Hashimoto, Yoshinobu Kawahara

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018