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Ryoma Sato

A Survey on The Expressive Power of Graph Neural Networks
2020 · Sato, Ryoma · arXiv (Cornell University) · 200
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Random Features Strengthen Graph Neural Networks
2021 · Ryoma Sato, Makoto Yamada, et al. · Society for Industrial and Applied Mathematics eBooks · 130
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Approximation Ratios of Graph Neural Networks for Combinatorial Problems
2019 · Sato, Ryoma, Yamada, Makoto, et al. · arXiv (Cornell University) · 46
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Embarrassingly Simple Text Watermarks
2023 · Sato, Ryoma, Takezawa, Yuki, et al. · arXiv (Cornell University) · 44
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Short-Term Precipitation Prediction with Skip-Connected PredNet
2018 · Ryoma Sato, Hisashi Kashima, et al. · Lecture notes in computer science · 35
Necessary and Sufficient Watermark for Large Language Models
2023 · Takezawa, Yuki, Sato, Ryoma, et al. · arXiv (Cornell University) · 27
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Fast and Robust Comparison of Probability Measures in Heterogeneous Spaces
2020 · Sato, Ryoma, Cuturi, Marco, et al. · arXiv (Cornell University) · 22
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Enumerating Fair Packages for Group Recommendations
2022 · Ryoma Sato · ACM International Conference on Web Search and Data Mining (WSDM) · 21
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Fast Unbalanced Optimal Transport on a Tree
2020 · Sato, Ryoma, Yamada, Makoto, et al. · arXiv (Cornell University) · 21
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Re-evaluating Word Mover's Distance
2021 · Sato, Ryoma, Yamada, Makoto, et al. · arXiv (Cornell University) · 18
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Parameter-free Clipped Gradient Descent Meets Polyak
2024 · Yuki Takezawa, Han Bao, et al. · neural information processing systems · 13
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Momentum Tracking: Momentum Acceleration for Decentralized Deep Learning on Heterogeneous Data
2022 · Takezawa, Yuki, Bao, Han, et al. · arXiv (Cornell University) · 12
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Beyond Exponential Graph: Communication-Efficient Topologies for Decentralized Learning via Finite-time Convergence
2023 · Yuki Takezawa, Ryoma Sato, et al. · neural information processing systems · 11
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Feature-Robust Optimal Transport for High-Dimensional Data
2023 · Mathis Petrovich, Chao Liang, et al. · Lecture notes in computer science · 10
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Constant Time Graph Neural Networks
2022 · Ryoma Sato, Makoto Yamada, et al. · ACM Transactions on Knowledge Discovery from Data · 10
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Private Recommender Systems: How Can Users Build Their Own Fair Recommender Systems without Log Data?
2022 · Ryoma Sato · Society for Industrial and Applied Mathematics eBooks · 8
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Approximating 1-Wasserstein Distance with Trees
2022 · Yamada, Makoto, Takezawa, Yuki, et al. · arXiv (Cornell University) · 7
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Supervised Tree-Wasserstein Distance
2021 · Takezawa, Yuki, Sato, Ryoma, et al. · arXiv (Cornell University) · 6
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Training-free Graph Neural Networks and the Power of Labels as Features
2024 · Sato, Ryoma · arXiv (Cornell University) · 5
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Retrieving Black-box Optimal Images from External Databases
2022 · Ryoma Sato · ACM International Conference on Web Search and Data Mining (WSDM) · 5
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Fixed Support Tree-Sliced Wasserstein Barycenter
2021 · Takezawa, Yuki, Sato, Ryoma, et al. · arXiv (Cornell University) · 5
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Poincare: Recommending Publication Venues via Treatment Effect Estimation
2022 · Ryoma Sato, Makoto Yamada, et al. · Journal of Informetrics · 4
Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure
2023 · Sato, Ryoma · arXiv (Cornell University) · 3
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CLEAR: A Fully User-side Image Search System
2022 · Ryoma Sato · ACM International Conference on Information and Knowledge Management (CIKM) · 3
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Towards Principled User-side Recommender Systems
2022 · Ryoma Sato · ACM International Conference on Information and Knowledge Management (CIKM) · 3
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Works count: 54
Citation count: 679
H-index: 12
I10-index: 15
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