Ryota Tomioka

Cited by

	All	Since 2016
Citations	6885	4560
h-index	33	25
i10-index	56	44

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20072008200920102011201220132014201520162017201820192020202125 68 105 178 280 279 364 471 476 504 647 888 1151 1343 14

Co-authors

Klaus-Robert MüllerGoogle Brain (on leave of Professor for Machine Learning, TU Berlin & Korea University, Seoul)Verified email at tu-berlin.de
Masashi SugiyamaDirector, RIKEN Center for Advanced Intelligence Project / Professor, The University of TokyoVerified email at k.u-tokyo.ac.jp
Taiji SuzukiThe University of TokyoVerified email at mist.i.u-tokyo.ac.jp
Benjamin BlankertzTechnische Universität Berlin, Neurotechnology groupVerified email at tu-berlin.de
Hisashi KashimaProfessor, Kyoto UniversityVerified email at i.kyoto-u.ac.jp
Sebastian NowozinPartner Researcher, Microsoft Research (Cambridge, UK)Verified email at microsoft.com
Milan VojnovicProfessor, Department of Statistics, LSEVerified email at lse.ac.uk
Kohei HayashiResearcher, Preferred NetworksVerified email at preferred.jp
Motoaki KawanabeSenior Researcher, Advanced Telecommunications Research Institute InternationalVerified email at atr.jp
Dan AlistarhIST AustriaVerified email at csail.mit.edu
Jerry LiMicrosoft ResearchVerified email at mit.edu
Behnam NeyshaburStaff Research Scientist, GoogleVerified email at google.com
Nathan SrebroProfessor, TTIC and University of ChicagoVerified email at ttic.edu
Guido NolteDept. of Neurophysiology and Pathophysiology, UKE, HamburgVerified email at uke.de
Botond CsekeVolkswagen Data LabVerified email at volkswagen.de
Kenji YamanishiThe University of TokyoVerified email at mist.i.u-tokyo.ac.jp
Stefan HaufeCharité - Universitätsmedizin BerlinVerified email at charite.de
Shinichi NakajimaMachine Learning Group, Technische Universität BerlinVerified email at tu-berlin.de
Diane BouchacourtFacebook AI ResearchVerified email at fb.com
Franz J. KiralyLecturer in StatisticsVerified email at ucl.ac.uk

Ryota Tomioka

Microsoft Research Cambridge

Verified email at microsoft.com - Homepage

Machine Learning Convex Optimization Neural Networks


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Optimizing spatial filters for robust EEG single-trial analysis B Blankertz, R Tomioka, S Lemm, M Kawanabe, KR Muller IEEE Signal processing magazine 25 (1), 41-56, 2007	1713	2007
f-gan: Training generative neural samplers using variational divergence minimization S Nowozin, B Cseke, R Tomioka Advances in Neural Information Processing Systems, 271-279, 2016	880	2016
QSGD: Communication-efficient SGD via gradient quantization and encoding D Alistarh, D Grubic, J Li, R Tomioka, M Vojnovic Advances in Neural Information Processing Systems, 1709-1720, 2017	527*	2017
Norm-based capacity control in neural networks B Neyshabur, R Tomioka, N Srebro Conference on Learning Theory, 1376-1401, 2015	287	2015
Invariant common spatial patterns: Alleviating nonstationarities in brain-computer interfacing B Blankertz, M Kawanabe, R Tomioka, F Hohlefeld, K Müller, VV Nikulin Advances in neural information processing systems, 113-120, 2008	257	2008
In search of the real inductive bias: On the role of implicit regularization in deep learning B Neyshabur, R Tomioka, N Srebro arXiv preprint arXiv:1412.6614, 2014	239	2014
Estimation of low-rank tensors via convex optimization R Tomioka, K Hayashi, H Kashima arXiv preprint arXiv:1010.0789, 2010	194	2010
A regularized discriminative framework for EEG analysis with application to brain–computer interface R Tomioka, KR Müller NeuroImage 49 (1), 415-432, 2010	165	2010
Statistical performance of convex tensor decomposition R Tomioka, T Suzuki, K Hayashi, H Kashima Advances in neural information processing systems 24, 972-980, 2011	162	2011
Tensor factorization using auxiliary information A Narita, K Hayashi, R Tomioka, H Kashima Data Mining and Knowledge Discovery 25 (2), 298-324, 2012	133	2012
Convex tensor decomposition via structured schatten norm regularization R Tomioka, T Suzuki Advances in neural information processing systems 26, 1331-1339, 2013	132	2013
Multi-level variational autoencoder: Learning disentangled representations from grouped observations D Bouchacourt, R Tomioka, S Nowozin Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018	129	2018
Discovering emerging topics in social streams via link-anomaly detection T Takahashi, R Tomioka, K Yamanishi IEEE Transactions on Knowledge and Data Engineering 26 (1), 120-130, 2012	116	2012
Modeling sparse connectivity between underlying brain sources for EEG/MEG S Haufe, R Tomioka, G Nolte, KR Müller, M Kawanabe IEEE transactions on biomedical engineering 57 (8), 1954-1963, 2010	107	2010
Logistic regression for single trial EEG classification R Tomioka, K Aihara, KR Müller Advances in neural information processing systems, 1377-1384, 2007	106	2007
Large-scale EEG/MEG source localization with spatial flexibility S Haufe, R Tomioka, T Dickhaus, C Sannelli, B Blankertz, G Nolte, ... NeuroImage 54 (2), 851-859, 2011	98	2011
Multivariate analysis of noise in genetic regulatory networks R Tomioka, H Kimura, TJ Kobayashi, K Aihara Journal of theoretical biology 229 (4), 501-521, 2004	97	2004
Super-Linear Convergence of Dual Augmented Lagrangian Algorithm for Sparsity Regularized Estimation. R Tomioka, T Suzuki, M Sugiyama Journal of Machine Learning Research 12 (5), 2011	90	2011
The algebraic combinatorial approach for low-rank matrix completion FJ Király, L Theran, R Tomioka The Journal of Machine Learning Research 16 (1), 1391-1436, 2015	88	2015
Geometry of optimization and implicit regularization in deep learning B Neyshabur, R Tomioka, R Salakhutdinov, N Srebro arXiv preprint arXiv:1705.03071, 2017	82	2017

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