Isao Ishikawa

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 34

Top Topics

Reproducing Kernel

Dynamical Systems

Reproducing Kernel Hilbert Space

Top Venues

J. Mach. Learn. Res.

Publications

Yuka Hashimoto, Sho Sonoda, Isao Ishikawa, Atsushi Nitanda, Taiji Suzuki
Koopman-based generalization bound: New aspect for full-rank weights. ICLR (2024)
Motoya Ohnishi, Isao Ishikawa, Kendall Lowrey, Masahiro Ikeda, Sham M. Kakade, Yoshinobu Kawahara
Koopman Spectrum Nonlinear Regulators and Efficient Online Learning. Trans. Mach. Learn. Res. 2024 (2024)
Isao Ishikawa
Finite-dimensional approximations of push-forwards on locally analytic functionals and truncation of least-squares polynomials. CoRR (2024)
Sho Sonoda, Isao Ishikawa, Masahiro Ikeda
A unified Fourier slice method to derive ridgelet transform for a variety of depth-2 neural networks. CoRR (2024)
Sho Sonoda, Yuka Hashimoto, Isao Ishikawa, Masahiro Ikeda
Constructive Universal Approximation Theorems for Deep Joint-Equivariant Networks by Schur's Lemma. CoRR (2024)
Isao Ishikawa, Yuka Hashimoto, Masahiro Ikeda, Yoshinobu Kawahara
Koopman operators with intrinsic observables in rigged reproducing kernel Hilbert spaces. CoRR (2024)
Hayato Chiba, Masahiro Ikeda, Isao Ishikawa
Generalized Eigenvalues of the Perron-Frobenius Operators of Symbolic Dynamical Systems. SIAM J. Appl. Dyn. Syst. 22 (4) (2023)
Sho Sonoda, Yuka Hashimoto, Isao Ishikawa, Masahiro Ikeda
Deep Ridgelet Transform: Voice with Koopman Operator Proves Universality of Formal Deep Networks. CoRR (2023)
Sho Sonoda, Hideyuki Ishi, Isao Ishikawa, Masahiro Ikeda
Joint Group Invariant Functions on Data-Parameter Domain Induce Universal Neural Networks. CoRR (2023)
Yuka Hashimoto, Sho Sonoda, Isao Ishikawa, Atsushi Nitanda, Taiji Suzuki
Koopman-Based Bound for Generalization: New Aspect of Neural Networks Regarding Nonlinear Noise Filtering. CoRR (2023)
Sho Sonoda, Isao Ishikawa, Masahiro Ikeda
Fully-Connected Network on Noncompact Symmetric Space and Ridgelet Transform based on Helgason-Fourier Analysis. CoRR (2022)
Motoya Ohnishi, Isao Ishikawa, Yuko Kuroki, Masahiro Ikeda
Dynamic Structure Estimation from Bandit Feedback. CoRR (2022)
Sho Sonoda, Isao Ishikawa, Masahiro Ikeda
Fully-Connected Network on Noncompact Symmetric Space and Ridgelet Transform based on Helgason-Fourier Analysis. ICML (2022)
Sho Sonoda, Isao Ishikawa, Masahiro Ikeda
Universality of group convolutional neural networks based on ridgelet analysis on groups. CoRR (2022)
Sho Sonoda, Isao Ishikawa, Masahiro Ikeda
Universality of Group Convolutional Neural Networks Based on Ridgelet Analysis on Groups. NeurIPS (2022)
Isao Ishikawa, Takeshi Teshima, Koichi Tojo, Kenta Oono, Masahiro Ikeda, Masashi Sugiyama
Universal approximation property of invertible neural networks. CoRR (2022)
Yuka Hashimoto, Isao Ishikawa, Masahiro Ikeda, Fuyuta Komura, Takeshi Katsura, Yoshinobu Kawahara
Reproducing kernel Hilbert C*-module and kernel mean embeddings. CoRR (2021)
Motoya Ohnishi, Isao Ishikawa, Kendall Lowrey, Masahiro Ikeda, Sham M. Kakade, Yoshinobu Kawahara
Koopman Spectrum Nonlinear Regulator and Provably Efficient Online Learning. CoRR (2021)
Sho Sonoda, Isao Ishikawa, Masahiro Ikeda
Ridge Regression with Over-parametrized Two-Layer Networks Converge to Ridgelet Spectrum. AISTATS (2021)
Yuka Hashimoto, Isao Ishikawa, Masahiro Ikeda, Fuyuta Komura, Takeshi Katsura, Yoshinobu Kawahara
Reproducing kernel Hilbert C*-module and kernel mean embeddings. J. Mach. Learn. Res. 22 (2021)
Sho Sonoda, Isao Ishikawa, Masahiro Ikeda
Ghosts in Neural Networks: Existence, Structure and Role of Infinite-Dimensional Null Space. CoRR (2021)
Naoya Hatano, Masahiro Ikeda, Isao Ishikawa, Yoshihiro Sawano
A global universality of two-layer neural networks with ReLU activations. CoRR (2020)
Takeshi Teshima, Isao Ishikawa, Koichi Tojo, Kenta Oono, Masahiro Ikeda, Masashi Sugiyama
Coupling-based Invertible Neural Networks Are Universal Diffeomorphism Approximators. NeurIPS (2020)
Yuka Hashimoto, Isao Ishikawa, Masahiro Ikeda, Yoichi Matsuo, Yoshinobu Kawahara
Krylov Subspace Method for Nonlinear Dynamical Systems with Random Noise. J. Mach. Learn. Res. 21 (2020)
Takeshi Teshima, Koichi Tojo, Masahiro Ikeda, Isao Ishikawa, Kenta Oono
Universal Approximation Property of Neural Ordinary Differential Equations. CoRR (2020)
Sho Sonoda, Isao Ishikawa, Masahiro Ikeda
Gradient Descent Converges to Ridgelet Spectrum. CoRR (2020)
Yuka Hashimoto, Isao Ishikawa, Masahiro Ikeda, Fuyuta Komura, Takeshi Katsura, Yoshinobu Kawahara
-Modules and Applications. CoRR (2020)
Yuka Hashimoto, Isao Ishikawa, Masahiro Ikeda, Fuyuta Komura, Yoshinobu Kawahara
Kernel Mean Embeddings of Von Neumann-Algebra-Valued Measures. CoRR (2020)
Takeshi Teshima, Isao Ishikawa, Koichi Tojo, Kenta Oono, Masahiro Ikeda, Masashi Sugiyama
Coupling-based Invertible Neural Networks Are Universal Diffeomorphism Approximators. CoRR (2020)
Isao Ishikawa, Akinori Tanaka, Masahiro Ikeda, Yoshinobu Kawahara
Metric on random dynamical systems with vector-valued reproducing kernel Hilbert spaces. CoRR (2019)
Yuka Hashimoto, Isao Ishikawa, Masahiro Ikeda, Yoichi Matsuo, Yoshinobu Kawahara
Krylov Subspace Method for Nonlinear Dynamical Systems with Random Noise. CoRR (2019)
Isao Ishikawa, Keisuke Fujii, Masahiro Ikeda, Yuka Hashimoto, Yoshinobu Kawahara
Metric on Nonlinear Dynamical Systems with Koopman Operators. CoRR (2018)
Isao Ishikawa, Keisuke Fujii, Masahiro Ikeda, Yuka Hashimoto, Yoshinobu Kawahara
Metric on Nonlinear Dynamical Systems with Perron-Frobenius Operators. NeurIPS (2018)
Sho Sonoda, Isao Ishikawa, Masahiro Ikeda, Kei Hagihara, Yoshihiro Sawano, Takuo Matsubara, Noboru Murata
Integral representation of the global minimizer. CoRR (2018)