Makoto Yamada

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Masashi SugiyamaDirector, RIKEN Center for Advanced Intelligence Project / Professor, The University of TokyoVerified email at k.u-tokyo.ac.jp
Yi ChangJilin UniversityVerified email at acm.org
Hisashi KashimaProfessor, Kyoto UniversityVerified email at i.kyoto-u.ac.jp
Ryoma SatoKyoto UniversityVerified email at ml.ist.i.kyoto-u.ac.jp
Tam LeAssistant Professor, The Institute of Statistical MathematicsVerified email at ism.ac.jp
Yao-Hung Hubert TsaiCarnegie Mellon University PhD StudentVerified email at andrew.cmu.edu
Song LiuSenior Lecturer in Statistical Science, University of Bristol, UKVerified email at bristol.ac.uk
Leonid SigalProfessor, University of British ColumbiaVerified email at cs.ubc.ca
Ruslan SalakhutdinovUPMC Professor, Machine Learning Department, CMUVerified email at cs.cmu.edu
Taiji SuzukiThe University of TokyoVerified email at mist.i.u-tokyo.ac.jp
Takafumi KanamoriTokyo Institute of TechnologyVerified email at c.titech.ac.jp
Dawei YinSenior Director of Search Science at Baidu, Inc.Verified email at baidu.com
Samuel KaskiProfessor, Aalto University and University of ManchesterVerified email at aalto.fi
Akisato KimuraNTT Communication Science LaboratoriesVerified email at ieee.org
Gang NiuRIKEN Center for Advanced Intelligence ProjectVerified email at postman.riken.jp
Yanbin LiuAustralian National UniversityVerified email at anu.edu.au
Wittawat JitkrittumGoogle ResearchVerified email at google.com
Denny WuUniversity of TorontoVerified email at cs.toronto.edu
Tomoharu IwataNTTVerified email at hco.ntt.co.jp
Yi YangZhejiang UniversityVerified email at zju.edu.cn

Makoto Yamada

Okinawa Institute of Science and Technology

Verified email at oist.jp - Homepage

Machine Learning Optimal transport kernel methods


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
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	538	2013
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	412	2018
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	299	2014
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	210	2013
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, 2022	187	2022
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	126	2019
Random features strengthen graph neural networks R Sato, M Yamada, H Kashima Proceedings of the 2021 SIAM International Conference on Data Mining (SDM …, 2021	119	2021
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	115	2018
Information-theoretic Semi-supervised Metric Learning via Entropy Regularization G Niu, B Dai, M Yamada, M Sugiyama Arxiv preprint arXiv:1206.4614, 2012	101	2012
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	90	2020
Approximation ratios of graph neural networks for combinatorial problems R Sato, M Yamada, H Kashima Advances in Neural Information Processing Systems 32, 2019	90	2019
Noise suppressing device M Yamada, K Kondo US Patent App. 13/005,138, 2011	84	2011
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	77	2016
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	77	2013
Persistence fisher kernel: A riemannian manifold kernel for persistence diagrams T Le, M Yamada Advances in Neural Information Processing Systems 31, 2018	73	2018
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	69	2019
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	69	2013
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	68	2018
Semi-supervised speaker identification under covariate shift M Yamada, M Sugiyama, T Matsui Signal Processing 90 (8), 2353-2361, 2010	67	2010
Tree-sliced variants of Wasserstein distances T Le, M Yamada, K Fukumizu, M Cuturi Advances in neural information processing systems 32, 2019	63	2019

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