Issei Sato
Issei Sato
University of Tokyo
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Cited by
Cited by
Year
Reducing wrong labels in distant supervision for relation extraction
S Takamatsu, I Sato, H Nakagawa
Proceedings of the 50th Annual Meeting of the Association for Computational …, 2012
2172012
Lipschitz-margin training: Scalable certification of perturbation invariance for deep neural networks
Y Tsuzuku, I Sato, M Sugiyama
arXiv preprint arXiv:1802.04034, 2018
1532018
Bayesian differential privacy on correlated data
B Yang, I Sato, H Nakagawa
Proceedings of the 2015 ACM SIGMOD international conference on Management of …, 2015
1312015
Ghost cytometry
S Ota, R Horisaki, Y Kawamura, M Ugawa, I Sato, K Hashimoto, ...
Science 360 (6394), 1246-1251, 2018
1102018
Does distributionally robust supervised learning give robust classifiers?
W Hu, G Niu, I Sato, M Sugiyama
International Conference on Machine Learning, 2029-2037, 2018
912018
Topic models with power-law using Pitman-Yor process
I Sato, H Nakagawa
Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010
902010
Deep neural network‐based computer‐assisted detection of cerebral aneurysms in MR angiography
T Nakao, S Hanaoka, Y Nomura, I Sato, M Nemoto, S Miki, E Maeda, ...
Journal of Magnetic Resonance Imaging 47 (4), 948-953, 2018
852018
Person name disambiguation by bootstrapping
M Yoshida, M Ikeda, S Ono, I Sato, H Nakagawa
Proceedings of the 33rd international ACM SIGIR conference on Research and …, 2010
772010
Approximation analysis of stochastic gradient Langevin dynamics by using Fokker-Planck equation and Ito process
I Sato, H Nakagawa
International Conference on Machine Learning, 982-990, 2014
702014
Generative adversarial nets from a density ratio estimation perspective
M Uehara, I Sato, M Suzuki, K Nakayama, Y Matsuo
arXiv preprint arXiv:1610.02920, 2016
692016
Person name disambiguation on the web by two-stage clustering
M Ikeda, S Ono, I Sato, M Yoshida, H Nakagawa
2nd Web People Search Evaluation Workshop (WePS 2009), 18th WWW Conference, 2009
492009
Rethinking collapsed variational Bayes inference for LDA
I Sato, H Nakagawa
arXiv preprint arXiv:1206.6435, 2012
452012
Learning from crowds and experts
H Kajino, Y Tsuboi, I Sato, H Kashima
Workshops at the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012
412012
Variational inference based on robust divergences
F Futami, I Sato, M Sugiyama
International Conference on Artificial Intelligence and Statistics, 813-822, 2018
382018
Sequential line search for efficient visual design optimization by crowds
Y Koyama, I Sato, D Sakamoto, T Igarashi
ACM Transactions on Graphics (TOG) 36 (4), 1-11, 2017
372017
ITC-UT: Tweet Categorization by Query Categorization for On-line Reputation Management.
M Yoshida, S Matsushima, S Ono, I Sato, H Nakagawa
CLEF (Notebook Papers/LABs/Workshops) 170, 2010
352010
Collusion-resistant privacy-preserving data mining
B Yang, H Nakagawa, I Sato, J Sakuma
Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010
302010
Practical collapsed variational Bayes inference for hierarchical Dirichlet process
I Sato, K Kurihara, H Nakagawa
Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012
292012
Unsupervised domain adaptation based on source-guided discrepancy
S Kuroki, N Charoenphakdee, H Bao, J Honda, I Sato, M Sugiyama
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 4122-4129, 2019
282019
Differential privacy without sensitivity
K Minami, HI Arai, I Sato, H Nakagawa
Advances in Neural Information Processing Systems, 956-964, 2016
272016
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Articles 1–20