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Makoto Yamada
Makoto Yamada
OIST & FlatMinima Inc.
Email verificata su oist.jp - Home page
Titolo
Citata da
Citata da
Anno
Change-point detection in time-series data by relative density-ratio estimation
S Liu, M Yamada, N Collier, M Sugiyama
Neural Networks 43, 72-83, 2013
6292013
Intelligent image-activated cell sorting
N Nitta, T Sugimura, A Isozaki, H Mikami, K Hiraki, S Sakuma, T Iino, ...
Cell 175 (1), 266-276. e13, 2018
5192018
Graphlime: Local interpretable model explanations for graph neural networks
Q Huang, M Yamada, Y Tian, D Singh, Y Chang
IEEE Transactions on Knowledge and Data Engineering 35 (7), 6968-6972, 2022
4492022
High-dimensional feature selection by feature-wise kernelized lasso
M Yamada, W Jitkrittum, L Sigal, EP Xing, M Sugiyama
Neural computation 26 (1), 185-207, 2014
3862014
Transformer dissection: a unified understanding of transformer's attention via the lens of kernel
YHH Tsai, S Bai, M Yamada, LP Morency, R Salakhutdinov
arXiv preprint arXiv:1908.11775, 2019
2752019
Relative density-ratio estimation for robust distribution comparison
M Yamada, T Suzuki, T Kanamori, H Hachiya, M Sugiyama
Neural computation 25 (5), 1324-1370, 2013
2722013
Random features strengthen graph neural networks
R Sato, M Yamada, H Kashima
Proceedings of the 2021 SIAM international conference on data mining (SDM …, 2021
2452021
Semantic correspondence as an optimal transport problem
Y Liu, L Zhu, M Yamada, Y Yang
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
1462020
High-throughput imaging flow cytometry by optofluidic time-stretch microscopy
C Lei, H Kobayashi, Y Wu, M Li, A Isozaki, A Yasumoto, H Mikami, T Ito, ...
Nature protocols 13 (7), 1603-1631, 2018
1462018
Approximation ratios of graph neural networks for combinatorial problems
R Sato, M Yamada, H Kashima
Advances in Neural Information Processing Systems 32, 2019
1292019
Noise suppressing device
M Yamada, K Kondo
US Patent App. 13/005,138, 2011
1212011
Information-theoretic Semi-supervised Metric Learning via Entropy Regularization
G Niu, B Dai, M Yamada, M Sugiyama
Arxiv preprint arXiv:1206.4614, 2012
1092012
Tree-sliced variants of Wasserstein distances
T Le, M Yamada, K Fukumizu, M Cuturi
Advances in neural information processing systems 32, 2019
972019
Persistence fisher kernel: A riemannian manifold kernel for persistence diagrams
T Le, M Yamada
Advances in neural information processing systems 31, 2018
962018
Change-point detection with feature selection in high-dimensional time-series data
M Yamada, A Kimura, F Naya, H Sawada
Twenty-Third International Joint Conference on Artificial Intelligence, 2013
942013
A practical guide to intelligent image-activated cell sorting
A Isozaki, H Mikami, K Hiramatsu, S Sakuma, Y Kasai, T Iino, T Yamano, ...
Nature protocols 14 (8), 2370-2415, 2019
902019
Beyond ranking: Optimizing whole-page presentation
Y Wang, D Yin, L Jie, P Wang, M Yamada, Y Chang, Q Mei
Proceedings of the Ninth ACM International Conference on Web Search and Data …, 2016
882016
Clustering-based anomaly detection in multi-view data
A Marcos Alvarez, M Yamada, A Kimura, T Iwata
Proceedings of the 22nd ACM international conference on Information …, 2013
872013
Block HSIC Lasso: model-free biomarker detection for ultra-high dimensional data
H Climente-González, CA Azencott, S Kaski, M Yamada
Bioinformatics 35 (14), i427-i435, 2019
862019
Ultra high-dimensional nonlinear feature selection for big biological data
M Yamada, J Tang, J Lugo-Martinez, E Hodzic, R Shrestha, A Saha, ...
IEEE Transactions on Knowledge and Data Engineering 30 (7), 1352-1365, 2018
852018
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
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