Yuka Hashimoto

Orcid: 0000-0002-1424-4298

According to our database1, Yuka Hashimoto authored at least 23 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Deep Koopman-layered Model with Universal Property Based on Toeplitz Matrices.
CoRR, 2024

Spectral Truncation Kernels: Noncommutativity in C<sup>*</sup>-algebraic Kernel Machines.
CoRR, 2024

Constructive Universal Approximation Theorems for Deep Joint-Equivariant Networks by Schur's Lemma.
CoRR, 2024

Quantum Circuit C<sup>*</sup>-algebra Net.
CoRR, 2024

Koopman operators with intrinsic observables in rigged reproducing kernel Hilbert spaces.
CoRR, 2024

C<sup>*</sup>-Algebraic Machine Learning: Moving in a New Direction.
CoRR, 2024

Position: C∗-Algebraic Machine Learning - Moving in a New Direction.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Koopman-based generalization bound: New aspect for full-rank weights.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Deep Ridgelet Transform: Voice with Koopman Operator Proves Universality of Formal Deep Networks.
CoRR, 2023

Koopman-Based Bound for Generalization: New Aspect of Neural Networks Regarding Nonlinear Noise Filtering.
CoRR, 2023

Noncommutative C<sup>*</sup>-algebra Net: Learning Neural Networks with Powerful Product Structure in C<sup>*</sup>-algebra.
CoRR, 2023

Deep learning with kernels through RKHM and the Perron-Frobenius operator.
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.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
A preconditioning technique for Krylov subspace methods in RKHSs.
J. Comput. Appl. Math., 2022

Learning in RKHM: a C<sup>*</sup>-Algebraic Twist for Kernel Machines.
CoRR, 2022

C<sup>*</sup>-algebra Net: A New Approach Generalizing Neural Network Parameters to C<sup>*</sup>-algebra.
CoRR, 2022

C*-algebra Net: A New Approach Generalizing Neural Network Parameters to C*-algebra.
Proceedings of the International Conference on Machine Learning, 2022

2021
Reproducing kernel Hilbert C*-module and kernel mean embeddings.
J. Mach. Learn. Res., 2021

2020
Krylov Subspace Method for Nonlinear Dynamical Systems with Random Noise.
J. Mach. Learn. Res., 2020

Kernel Mean Embeddings of Von Neumann-Algebra-Valued Measures.
CoRR, 2020

Analysis via Orthonormal Systems in Reproducing Kernel Hilbert C<sup>*</sup>-Modules and Applications.
CoRR, 2020

2018
Metric on Nonlinear Dynamical Systems with Koopman Operators.
CoRR, 2018

Metric on Nonlinear Dynamical Systems with Perron-Frobenius Operators.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018


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