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2020 – today
- 2023
[c18]Ryoma Sato:
Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure. ICML 2023: 30062-30079- [c17]Ryoma Sato
:
Active Learning from the Web. WWW 2023: 1616-1625 - [i23]Ryoma Sato:
Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure. CoRR abs/2301.10956 (2023) - [i22]Yuki Takezawa, Ryoma Sato, Han Bao, Kenta Niwa, Makoto Yamada:
Beyond Exponential Graph: Communication-Efficient Topologies for Decentralized Learning via Finite-time Convergence. CoRR abs/2305.11420 (2023) - 2022
- [j3]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Poincare: Recommending Publication Venues via Treatment Effect Estimation. J. Informetrics 16(2): 101283 (2022) - [j2]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Constant Time Graph Neural Networks. ACM Trans. Knowl. Discov. Data 16(5): 92:1-92:31 (2022) - [j1]Makoto Yamada, Yuki Takezawa, Ryoma Sato, Han Bao, Zornitsa Kozareva, Sujith Ravi:
Approximating 1-Wasserstein Distance with Trees. Trans. Mach. Learn. Res. 2022 (2022) - [c16]Yuki Takezawa, Ryoma Sato, Zornitsa Kozareva, Sujith Ravi, Makoto Yamada:
Fixed Support Tree-Sliced Wasserstein Barycenter. AISTATS 2022: 1120-1137 - [c15]Ryoma Sato:
Towards Principled User-side Recommender Systems. CIKM 2022: 1757-1766 - [c14]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Twin Papers: A Simple Framework of Causal Inference for Citations via Coupling. CIKM 2022: 4444-4448 - [c13]Ryoma Sato:
CLEAR: A Fully User-side Image Search System. CIKM 2022: 4970-4974 - [c12]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Re-evaluating Word Mover's Distance. ICML 2022: 19231-19249 - [c11]Ryoma Sato:
Word Tour: One-dimensional Word Embeddings via the Traveling Salesman Problem. NAACL-HLT 2022: 2166-2172 - [c10]Mathis Petrovich, Chao Liang, Ryoma Sato, Yanbin Liu, Yao-Hung Hubert Tsai, Linchao Zhu, Yi Yang, Ruslan Salakhutdinov, Makoto Yamada:
Feature-Robust Optimal Transport for High-Dimensional Data. ECML/PKDD (5) 2022: 291-307 - [c9]Ryoma Sato:
Private Recommender Systems: How Can Users Build Their Own Fair Recommender Systems without Log Data? SDM 2022: 549-557 - [c8]Ryoma Sato:
Enumerating Fair Packages for Group Recommendations. WSDM 2022: 870-878 - [c7]Ryoma Sato:
Retrieving Black-box Optimal Images from External Databases. WSDM 2022: 879-887 - [i21]Ryoma Sato:
Word Tour: One-dimensional Word Embeddings via the Traveling Salesman Problem. CoRR abs/2205.01954 (2022) - [i20]Ryoma Sato:
CLEAR: A Fully User-side Image Search System. CoRR abs/2206.08521 (2022) - [i19]Makoto Yamada, Yuki Takezawa, Ryoma Sato, Han Bao, Zornitsa Kozareva, Sujith Ravi:
Approximating 1-Wasserstein Distance with Trees. CoRR abs/2206.12116 (2022) - [i18]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Twin Papers: A Simple Framework of Causal Inference for Citations via Coupling. CoRR abs/2208.09862 (2022) - [i17]Ryoma Sato:
Towards Principled User-side Recommender Systems. CoRR abs/2208.09864 (2022) - [i16]Yuki Takezawa, Han Bao, Kenta Niwa, Ryoma Sato, Makoto Yamada:
Momentum Tracking: Momentum Acceleration for Decentralized Deep Learning on Heterogeneous Data. CoRR abs/2209.15505 (2022) - [i15]Ryoma Sato:
Active Learning from the Web. CoRR abs/2210.08205 (2022) - 2021
- [c6]Yuki Takezawa, Ryoma Sato, Makoto Yamada:
Supervised Tree-Wasserstein Distance. ICML 2021: 10086-10095 - [c5]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Random Features Strengthen Graph Neural Networks. SDM 2021: 333-341 - [i14]Yuki Takezawa, Ryoma Sato, Makoto Yamada:
Supervised Tree-Wasserstein Distance. CoRR abs/2101.11520 (2021) - [i13]Ryoma Sato:
Private Recommender Systems: How Can Users Build Their Own Fair Recommender Systems without Log Data? CoRR abs/2105.12353 (2021) - [i12]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Re-evaluating Word Mover's Distance. CoRR abs/2105.14403 (2021) - [i11]Ryoma Sato:
Enumerating Fair Packages for Group Recommendations. CoRR abs/2105.14423 (2021) - [i10]Yuki Takezawa, Ryoma Sato, Zornitsa Kozareva, Sujith Ravi, Makoto Yamada:
Fixed Support Tree-Sliced Wasserstein Barycenter. CoRR abs/2109.03431 (2021) - [i9]Ryoma Sato:
Retrieving Black-box Optimal Images from External Databases. CoRR abs/2112.14921 (2021) - 2020
- [c4]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Fast Unbalanced Optimal Transport on a Tree. NeurIPS 2020 - [i8]Ryoma Sato, Marco Cuturi, Makoto Yamada, Hisashi Kashima:
Fast and Robust Comparison of Probability Measures in Heterogeneous Spaces. CoRR abs/2002.01615 (2020) - [i7]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Random Features Strengthen Graph Neural Networks. CoRR abs/2002.03155 (2020) - [i6]Ryoma Sato:
A Survey on The Expressive Power of Graph Neural Networks. CoRR abs/2003.04078 (2020) - [i5]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Fast Unbalanced Optimal Transport on Tree. CoRR abs/2006.02703 (2020) - [i4]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Poincare: Recommending Publication Venues via Treatment Effect Estimation. CoRR abs/2010.09157 (2020)
2010 – 2019
- 2019
- [c3]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Learning to Sample Hard Instances for Graph Algorithms. ACML 2019: 503-518 - [c2]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Approximation Ratios of Graph Neural Networks for Combinatorial Problems. NeurIPS 2019: 4083-4092 - [i3]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Constant Time Graph Neural Networks. CoRR abs/1901.07868 (2019) - [i2]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Learning to Find Hard Instances of Graph Problems. CoRR abs/1902.09700 (2019) - [i1]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Approximation Ratios of Graph Neural Networks for Combinatorial Problems. CoRR abs/1905.10261 (2019) - 2018
- [c1]Ryoma Sato, Hisashi Kashima, Takehiro Yamamoto:
Short-Term Precipitation Prediction with Skip-Connected PredNet. ICANN (3) 2018: 373-382
Coauthor Index
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last updated on 2023-10-01 02:01 CEST by the dblp team
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