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Sho Sonoda
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2020 – today
- 2024
- [c10]Yuka Hashimoto, Sho Sonoda, Isao Ishikawa, Atsushi Nitanda, Taiji Suzuki:
Koopman-based generalization bound: New aspect for full-rank weights. ICLR 2024 - [i23]Toshinori Kitamura, Tadashi Kozuno, Masahiro Kato, Yuki Ichihara, Soichiro Nishimori, Akiyoshi Sannai, Sho Sonoda, Wataru Kumagai, Yutaka Matsuo:
A Policy Gradient Primal-Dual Algorithm for Constrained MDPs with Uniform PAC Guarantees. CoRR abs/2401.17780 (2024) - [i22]Sho Sonoda, Isao Ishikawa, Masahiro Ikeda:
A unified Fourier slice method to derive ridgelet transform for a variety of depth-2 neural networks. CoRR abs/2402.15984 (2024) - [i21]Sho Sonoda, Yuka Hashimoto, Isao Ishikawa, Masahiro Ikeda:
Constructive Universal Approximation Theorems for Deep Joint-Equivariant Networks by Schur's Lemma. CoRR abs/2405.13682 (2024) - 2023
- [j3]Kaito Watanabe
, Kotaro Sakamoto, Ryo Karakida, Sho Sonoda, Shun-ichi Amari:
Deep learning in random neural fields: Numerical experiments via neural tangent kernel. Neural Networks 160: 148-163 (2023) - [c9]Ming Li, Sho Sonoda, Feilong Cao, Yu Guang Wang, Jiye Liang:
How Powerful are Shallow Neural Networks with Bandlimited Random Weights? ICML 2023: 19960-19981 - [c8]Hayata Yamasaki, Sathyawageeswar Subramanian, Satoshi Hayakawa, Sho Sonoda:
Quantum Ridgelet Transform: Winning Lottery Ticket of Neural Networks with Quantum Computation. ICML 2023: 39008-39034 - [i20]Hayata Yamasaki, Sathyawageeswar Subramanian, Satoshi Hayakawa, Sho Sonoda:
Quantum Ridgelet Transform: Winning Lottery Ticket of Neural Networks with Quantum Computation. CoRR abs/2301.11936 (2023) - [i19]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 abs/2302.05825 (2023) - [i18]Ryutaro Yamauchi, Sho Sonoda, Akiyoshi Sannai, Wataru Kumagai:
LPML: LLM-Prompting Markup Language for Mathematical Reasoning. CoRR abs/2309.13078 (2023) - [i17]Sho Sonoda, Yuka Hashimoto, Isao Ishikawa, Masahiro Ikeda:
Deep Ridgelet Transform: Voice with Koopman Operator Proves Universality of Formal Deep Networks. CoRR abs/2310.03529 (2023) - [i16]Sho Sonoda, Hideyuki Ishi, Isao Ishikawa, Masahiro Ikeda:
Joint Group Invariant Functions on Data-Parameter Domain Induce Universal Neural Networks. CoRR abs/2310.03530 (2023) - 2022
- [c7]Sho Sonoda, Isao Ishikawa, Masahiro Ikeda:
Fully-Connected Network on Noncompact Symmetric Space and Ridgelet Transform based on Helgason-Fourier Analysis. ICML 2022: 20405-20422 - [c6]Sho Sonoda, Isao Ishikawa, Masahiro Ikeda:
Universality of Group Convolutional Neural Networks Based on Ridgelet Analysis on Groups. NeurIPS 2022 - [i15]Kaito Watanabe, Kotaro Sakamoto, Ryo Karakida, Sho Sonoda, Shun-ichi Amari:
Deep Learning in Random Neural Fields: Numerical Experiments via Neural Tangent Kernel. CoRR abs/2202.05254 (2022) - [i14]Sho Sonoda, Isao Ishikawa
, Masahiro Ikeda:
Fully-Connected Network on Noncompact Symmetric Space and Ridgelet Transform based on Helgason-Fourier Analysis. CoRR abs/2203.01631 (2022) - [i13]Sho Sonoda, Isao Ishikawa
, Masahiro Ikeda:
Universality of group convolutional neural networks based on ridgelet analysis on groups. CoRR abs/2205.14819 (2022) - 2021
- [c5]Sho Sonoda, Isao Ishikawa, Masahiro Ikeda:
Ridge Regression with Over-parametrized Two-Layer Networks Converge to Ridgelet Spectrum. AISTATS 2021: 2674-2682 - [c4]Stefano Massaroli, Michael Poli, Sho Sonoda, Taiji Suzuki, Jinkyoo Park, Atsushi Yamashita, Hajime Asama:
Differentiable Multiple Shooting Layers. NeurIPS 2021: 16532-16544 - [i12]Stefano Massaroli, Michael Poli, Sho Sonoda, Taiji Suzuki, Jinkyoo Park, Atsushi Yamashita, Hajime Asama:
Differentiable Multiple Shooting Layers. CoRR abs/2106.03885 (2021) - [i11]Sho Sonoda, Isao Ishikawa, Masahiro Ikeda:
Ghosts in Neural Networks: Existence, Structure and Role of Infinite-Dimensional Null Space. CoRR abs/2106.04770 (2021) - [i10]Hayata Yamasaki, Sho Sonoda:
Exponential Error Convergence in Data Classification with Optimized Random Features: Acceleration by Quantum Machine Learning. CoRR abs/2106.09028 (2021) - 2020
- [c3]Hayata Yamasaki, Sathyawageeswar Subramanian, Sho Sonoda, Masato Koashi:
Learning with Optimized Random Features: Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rank Assumptions. NeurIPS 2020 - [i9]Hayata Yamasaki, Sathyawageeswar Subramanian, Sho Sonoda, Masato Koashi:
Fast Quantum Algorithm for Learning with Optimized Random Features. CoRR abs/2004.10756 (2020) - [i8]Sho Sonoda, Isao Ishikawa, Masahiro Ikeda:
Gradient Descent Converges to Ridgelet Spectrum. CoRR abs/2007.03441 (2020) - [i7]Sho Sonoda, Ming Li, Feilong Cao, Changqin Huang, Yu Guang Wang:
On the Approximation Lower Bound for Neural Nets with Random Weights. CoRR abs/2008.08427 (2020)
2010 – 2019
- 2019
- [j2]Sho Sonoda, Noboru Murata:
Transport Analysis of Infinitely Deep Neural Network. J. Mach. Learn. Res. 20: 2:1-2:52 (2019) - [i6]Sho Sonoda:
Numerical Integration Method for Training Neural Network. CoRR abs/1902.00648 (2019) - 2018
- [j1]Sho Sonoda
, Keita Nakamura, Yuki Kaneda, Hideitsu Hino
, Shotaro Akaho
, Noboru Murata
, Eri Miyauchi, Masahiro Kawasaki:
EEG dipole source localization with information criteria for multiple particle filters. Neural Networks 108: 68-82 (2018) - [c2]Keita Nakamura, Sho Sonoda, Hideitsu Hino, Masahiro Kawasaki, Shotaro Akaho
, Noboru Murata
:
Localizing Current Dipoles from EEG Data Using a Birth-Death Process. BIBM 2018: 2645-2651 - [i5]Sho Sonoda, Isao Ishikawa, Masahiro Ikeda, Kei Hagihara, Yoshihiro Sawano, Takuo Matsubara, Noboru Murata:
Integral representation of the global minimizer. CoRR abs/1805.07517 (2018) - 2017
- [i4]Sho Sonoda, Noboru Murata:
Transportation analysis of denoising autoencoders: a novel method for analyzing deep neural networks. CoRR abs/1712.04145 (2017) - 2016
- [i3]Sho Sonoda, Noboru Murata:
Decoding Stacked Denoising Autoencoders. CoRR abs/1605.02832 (2016) - 2015
- [i2]Sho Sonoda, Noboru Murata:
Neural Network with Unbounded Activations is Universal Approximator. CoRR abs/1505.03654 (2015) - 2014
- [c1]Sho Sonoda
, Noboru Murata
:
Sampling Hidden Parameters from Oracle Distribution. ICANN 2014: 539-546 - 2013
- [i1]Sho Sonoda, Noboru Murata:
Nonparametric Weight Initialization of Neural Networks via Integral Representation. CoRR abs/1312.6461 (2013)
Coauthor Index
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last updated on 2024-08-08 19:19 CEST by the dblp team
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