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Issei Sato
Issei Sato
Verified email at g.ecc.u-tokyo.ac.jp
Title
Cited by
Cited by
Year
Lipschitz-margin training: Scalable certification of perturbation invariance for deep neural networks
Y Tsuzuku, I Sato, M Sugiyama
Advances in neural information processing systems 31, 2018
3092018
Does distributionally robust supervised learning give robust classifiers?
W Hu, G Niu, I Sato, M Sugiyama
International Conference on Machine Learning, 2029-2037, 2018
2972018
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
2562012
Ghost cytometry
S Ota, R Horisaki, Y Kawamura, M Ugawa, I Sato, K Hashimoto, ...
Science 360 (6394), 1246-1251, 2018
2192018
Bayesian differential privacy on correlated data
B Yang, I Sato, H Nakagawa
Proceedings of the 2015 ACM SIGMOD international conference on Management of …, 2015
2122015
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
1852018
A diffusion theory for deep learning dynamics: Stochastic gradient descent exponentially favors flat minima
Z Xie, I Sato, M Sugiyama
arXiv preprint arXiv:2002.03495, 2020
1242020
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
1032016
Topic models with power-law using Pitman-Yor process
I Sato, H Nakagawa
Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010
1012010
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
942014
Few-shot domain adaptation by causal mechanism transfer
T Teshima, I Sato, M Sugiyama
International Conference on Machine Learning, 9458-9469, 2020
892020
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
872010
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
842017
Variational inference based on robust divergences
F Futami, I Sato, M Sugiyama
International Conference on Artificial Intelligence and Statistics, 813-822, 2018
722018
Sequential gallery for interactive visual design optimization
Y Koyama, I Sato, M Goto
ACM Transactions on Graphics (TOG) 39 (4), 88: 1-88: 12, 2020
682020
Normalized flat minima: Exploring scale invariant definition of flat minima for neural networks using pac-bayesian analysis
Y Tsuzuku, I Sato, M Sugiyama
International Conference on Machine Learning, 9636-9647, 2020
652020
Differential privacy without sensitivity
K Minami, HI Arai, I Sato, H Nakagawa
Advances in Neural Information Processing Systems 29, 2016
622016
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
612019
On the structural sensitivity of deep convolutional networks to the directions of fourier basis functions
Y Tsuzuku, I Sato
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
582019
Mining words in the minds of second language learners for learner-specific word difficulty
Y Ehara, I Sato, H Oiwa, H Nakagawa
Journal of Information Processing 26, 267-275, 2018
552018
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Articles 1–20