Sonoda, Sho

12 publications

ICML 2025 Deep Ridgelet Transform and Unified Universality Theorem for Deep and Shallow Joint-Group-Equivariant Machines Sho Sonoda, Yuka Hashimoto, Isao Ishikawa, Masahiro Ikeda

ICLR 2024 Koopman-Based Generalization Bound: New Aspect for Full-Rank Weights Yuka Hashimoto, Sho Sonoda, Isao Ishikawa, Atsushi Nitanda, Taiji Suzuki

NeurIPSW 2023 Deep Ridgelet Transform: Voice with Koopman Operator Constructively Proves Universality of Formal Deep Networks Sho Sonoda, Yuka Hashimoto, Isao Ishikawa, Masahiro Ikeda

ICML 2023 How Powerful Are Shallow Neural Networks with Bandlimited Random Weights? Ming Li, Sho Sonoda, Feilong Cao, Yu Guang Wang, Jiye Liang

NeurIPSW 2023 Joint Group Invariant Functions on Data-Parameter Domain Induce Universal Neural Networks Sho Sonoda, Hideyuki Ishi, Isao Ishikawa, Masahiro Ikeda

ICML 2023 Quantum Ridgelet Transform: Winning Lottery Ticket of Neural Networks with Quantum Computation Hayata Yamasaki, Sathyawageeswar Subramanian, Satoshi Hayakawa, Sho Sonoda

ICML 2022 Fully-Connected Network on Noncompact Symmetric Space and Ridgelet Transform Based on Helgason-Fourier Analysis Sho Sonoda, Isao Ishikawa, Masahiro Ikeda

NeurIPS 2022 Universality of Group Convolutional Neural Networks Based on Ridgelet Analysis on Groups Sho Sonoda, Isao Ishikawa, Masahiro Ikeda

AISTATS 2021 Ridge Regression with Over-Parametrized Two-Layer Networks Converge to Ridgelet Spectrum Sho Sonoda, Isao Ishikawa, Masahiro Ikeda

NeurIPS 2021 Differentiable Multiple Shooting Layers Stefano Massaroli, Michael Poli, Sho Sonoda, Taiji Suzuki, Jinkyoo Park, Atsushi Yamashita, Hajime Asama

NeurIPS 2020 Learning with Optimized Random Features: Exponential Speedup by Quantum Machine Learning Without Sparsity and Low-Rank Assumptions Hayata Yamasaki, Sathyawageeswar Subramanian, Sho Sonoda, Masato Koashi

JMLR 2019 Transport Analysis of Infinitely Deep Neural Network Sho Sonoda, Noboru Murata