Sho Sonoda
10 papers · 2019–2025 · 5 venues · across top CS/AI venues
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Achievements
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(5)
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(63)
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Research topics
Machine Learning
(10)
Deep Learning
(9)
Optimization & Theory Β· Machine Learning
(9)
Architectures
(6)
Core Methods
(4)
Optimization & Theory Β· Deep Learning
(4)
Artificial Intelligence
(2)
Interdisciplinary
(2)
Mathematics & Optimization
(2)
Learning Paradigms
(2)
Science
(2)
Application Areas
(1)
Learning Types
(1)
Mathematics
(1)
Optimization
(1)
Keywords
ridgelet transform
(5)
neural network
(3)
ridgelet analysis
(2)
weight matrix
(2)
quantum machine learning
(2)
deep learning theory
(1)
universal approximation
(1)
stochastic gradient descent
(1)
group theory
(1)
geometric deep learning
(1)
neural network theory
(1)
time series classification
(1)
optimal control
(1)
riemannian manifold
(1)
ridge regression
(1)
deep neural network
(1)
convolutional neural network
(1)
denoising autoencoder
(1)
inductive bia
(1)
generalization bound
(1)
Papers
Deep Ridgelet Transform and Unified Universality Theorem for Deep and Shallow Joint-Group-Equivariant Machines
ICML 2025
Koopman-based generalization bound: New aspect for full-rank weights
ICLR 2024
How Powerful are Shallow Neural Networks with Bandlimited Random Weights?
ICML 2023
Quantum Ridgelet Transform: Winning Lottery Ticket of Neural Networks with Quantum Computation
ICML 2023
Fully-Connected Network on Noncompact Symmetric Space and Ridgelet Transform based on Helgason-Fourier Analysis
ICML 2022
Universality of Group Convolutional Neural Networks Based on Ridgelet Analysis on Groups
NeurIPS 2022
Differentiable Multiple Shooting Layers
NeurIPS 2021
Ridge Regression with Over-parametrized Two-Layer Networks Converge to Ridgelet Spectrum
AISTATS 2021
Learning with Optimized Random Features: Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rank Assumptions
NeurIPS 2020
Transport Analysis of Infinitely Deep Neural Network
JMLR 2019