フォロー
Ryoma Sato
Ryoma Sato
確認したメール アドレス: ml.ist.i.kyoto-u.ac.jp - ホームページ
タイトル
引用先
引用先
Random features strengthen graph neural networks
R Sato, M Yamada, H Kashima
Proceedings of the 2021 SIAM international conference on data mining (SDM …, 2021
2022021
A survey on the expressive power of graph neural networks
R Sato
arXiv preprint arXiv:2003.04078, 2020
1802020
Approximation ratios of graph neural networks for combinatorial problems
R Sato, M Yamada, H Kashima
Advances in Neural Information Processing Systems 32, 2019
1182019
Fast unbalanced optimal transport on a tree
R Sato, M Yamada, H Kashima
Advances in neural information processing systems 33, 19039-19051, 2020
282020
Short-term precipitation prediction with skip-connected prednet
R Sato, H Kashima, T Yamamoto
Artificial Neural Networks and Machine Learning–ICANN 2018: 27th …, 2018
272018
Re-evaluating word mover’s distance
R Sato, M Yamada, H Kashima
International Conference on Machine Learning, 19231-19249, 2022
232022
Enumerating fair packages for group recommendations
R Sato
Proceedings of the Fifteenth ACM International Conference on Web Search and …, 2022
172022
Fast and robust comparison of probability measures in heterogeneous spaces
R Sato, M Cuturi, M Yamada, H Kashima
arXiv preprint arXiv:2002.01615, 2020
172020
Fixed support tree-sliced Wasserstein barycenter
Y Takezawa, R Sato, Z Kozareva, S Ravi, M Yamada
arXiv preprint arXiv:2109.03431, 2021
142021
Supervised tree-wasserstein distance
Y Takezawa, R Sato, M Yamada
International Conference on Machine Learning, 10086-10095, 2021
112021
Momentum tracking: Momentum acceleration for decentralized deep learning on heterogeneous data
Y Takezawa, H Bao, K Niwa, R Sato, M Yamada
arXiv preprint arXiv:2209.15505, 2022
82022
Feature-robust optimal transport for high-dimensional data
M Petrovich, C Liang, R Sato, Y Liu, YHH Tsai, L Zhu, Y Yang, ...
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2022
82022
Private Recommender Systems: How Can Users Build Their Own Fair Recommender Systems without Log Data?
R Sato
Proceedings of the 2022 SIAM International Conference on Data Mining (SDM …, 2022
82022
Approximating 1-wasserstein distance with trees
M Yamada, Y Takezawa, R Sato, H Bao, Z Kozareva, S Ravi
arXiv preprint arXiv:2206.12116, 2022
72022
Constant time graph neural networks
R Sato, M Yamada, H Kashima
ACM Transactions on Knowledge Discovery from Data (TKDD) 16 (5), 1-31, 2022
72022
Retrieving black-box optimal images from external databases
R Sato
Proceedings of the Fifteenth ACM International Conference on Web Search and …, 2022
72022
Clear: A fully user-side image search system
R Sato
Proceedings of the 31st ACM International Conference on Information …, 2022
62022
Embarrassingly simple text watermarks
R Sato, Y Takezawa, H Bao, K Niwa, M Yamada
arXiv preprint arXiv:2310.08920, 2023
52023
Necessary and sufficient watermark for large language models
Y Takezawa, R Sato, H Bao, K Niwa, M Yamada
arXiv preprint arXiv:2310.00833, 2023
52023
Graph neural networks can recover the hidden features solely from the graph structure
R Sato
International Conference on Machine Learning, 30062-30079, 2023
52023
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