Optimizing Spectral Filters for Single Trial EEG Classification. - Ryota Tomioka; Guido Dornhege; Guido Nolte; Kazuyuki Aihara; Klaus-Robert Müller (DAGM-Symposium, 2006)

Logistic Regression for Single Trial EEG Classification. - Ryota Tomioka; Kazuyuki Aihara; Klaus-Robert Müller (NIPS, 2006)

Classifying matrices with a spectral regularization. - Ryota Tomioka; Kazuyuki Aihara (ICML, 2007)

Invariant Common Spatial Patterns: Alleviating Nonstationarities in Brain-Computer Interfacing. - Benjamin Blankertz; Motoaki Kawanabe; Ryota Tomioka; Friederike U. Hohlefeld; Vadim V. Nikulin; Klaus-Robert Müller (NIPS, 2007)

Optimizing Spatial filters for Robust EEG Single-Trial Analysis. - Benjamin Blankertz; Ryota Tomioka; Steven Lemm; Motoaki Kawanabe; Klaus-Robert Müller (IEEE Signal Process. Mag., 2008)

Dual-Augmented Lagrangian Method for Efficient Sparse Reconstruction. - Ryota Tomioka; Masashi Sugiyama (IEEE Signal Process. Lett., 2009)

A Fast Augmented Lagrangian Algorithm for Learning Low-Rank Matrices. - Ryota Tomioka; Taiji Suzuki; Masashi Sugiyama; Hisashi Kashima (ICML, 2010)

Global Analytic Solution for Variational Bayesian Matrix Factorization. - Shinichi Nakajima; Masashi Sugiyama; Ryota Tomioka (NIPS, 2010)

Regularization Strategies and Empirical Bayesian Learning for MKL. - Ryota Tomioka; Taiji Suzuki (CoRR, 2010)

Output Divergence Criterion for Active Learning in Collaborative Settings. - Neil Rubens; Ryota Tomioka; Masashi Sugiyama (Inf. Media Technol., 2010)

A regularized discriminative framework for EEG analysis with application to brain-computer interface. - Ryota Tomioka; Klaus-Robert Müller (NeuroImage, 2010)

Modeling Sparse Connectivity Between Underlying Brain Sources for EEG/MEG. - Stefan Haufe; Ryota Tomioka; Guido Nolte; Klaus-Robert Müller; Motoaki Kawanabe (IEEE Trans. Biomed. Eng., 2010)

A New Multi-task Learning Method for Personalized Activity Recognition. - Xu Sun 001; Hisashi Kashima; Ryota Tomioka; Naonori Ueda; Ping Li 001 (ICDM, 2011)

Statistical Performance of Convex Tensor Decomposition. - Ryota Tomioka; Taiji Suzuki; Kohei Hayashi; Hisashi Kashima (NIPS, 2011)

Large Scale Real-Life Action Recognition Using Conditional Random Fields with Stochastic Training. - Xu Sun 001; Hisashi Kashima; Ryota Tomioka; Naonori Ueda (PAKDD (2), 2011)

Real-Time Change-Point Detection Using Sequentially Discounting Normalized Maximum Likelihood Coding. - Yasuhiro Urabe; Kenji Yamanishi; Ryota Tomioka; Hiroki Iwai (PAKDD (2), 2011)

Super-Linear Convergence of Dual Augmented Lagrangian Algorithm for Sparsity Regularized Estimation. - Ryota Tomioka; Taiji Suzuki; Masashi Sugiyama (J. Mach. Learn. Res., 2011)

SpicyMKL: a fast algorithm for Multiple Kernel Learning with thousands of kernels. - Taiji Suzuki; Ryota Tomioka (Mach. Learn., 2011)

Large-scale EEG/MEG source localization with spatial flexibility. - Stefan Haufe; Ryota Tomioka; Thorsten Dickhaus; Claudia Sannelli; Benjamin Blankertz; Guido Nolte; Klaus-Robert Müller (NeuroImage, 2011)

A Combinatorial Algebraic Approach for the Identifiability of Low-Rank Matrix Completion. - Franz J. Király; Ryota Tomioka (ICML, 2012)

Perfect Dimensionality Recovery by Variational Bayesian PCA. - Shinichi Nakajima; Ryota Tomioka; Masashi Sugiyama; S. Derin Babacan (NIPS, 2012)

The Algebraic Combinatorial Approach for Low-Rank Matrix Completion - Franz J. Király; Louis Theran; Ryota Tomioka; Takeaki Uno (CoRR, 2012)

Tensor factorization using auxiliary information. - Atsuhiro Narita; Kohei Hayashi; Ryota Tomioka; Hisashi Kashima (Data Min. Knowl. Discov., 2012)

Self-measuring Similarity for Multi-task Gaussian Process. - Kohei Hayashi; Takashi Takenouchi; Ryota Tomioka; Hisashi Kashima (ICML Unsupervised and Transfer Learning, 2012)

A Bayesian Analysis of the Radioactive Releases of Fukushima. - Ryota Tomioka; Morten Mørup (AISTATS, 2012)

Quantitative Prediction of Glaucomatous Visual Field Loss from Few Measurements. - Zenghan Liang; Ryota Tomioka; Hiroshi Murata; Ryo Asaoka; Kenji Yamanishi (ICDM, 2013)

Non-negative Multiple Tensor Factorization. - Koh Takeuchi; Ryota Tomioka; Katsuhiko Ishiguro; Akisato Kimura; Hiroshi Sawada (ICDM, 2013)

Infinite Positive Semidefinite Tensor Factorization for Source Separation of Mixture Signals. - Kazuyoshi Yoshii; Ryota Tomioka; Daichi Mochihashi; Masataka Goto (ICML (3), 2013)

Beyond NMF: Time-Domain Audio Source Separation without Phase Reconstruction. - Kazuyoshi Yoshii; Ryota Tomioka; Daichi Mochihashi; Masataka Goto (ISMIR, 2013)

Convex Tensor Decomposition via Structured Schatten Norm Regularization. - Ryota Tomioka; Taiji Suzuki (NIPS, 2013)

Global analytic solution of fully-observed variational Bayesian matrix factorization. - Shinichi Nakajima; Masashi Sugiyama; S. Derin Babacan; Ryota Tomioka (J. Mach. Learn. Res., 2013)

Multitask learning meets tensor factorization: task imputation via convex optimization. - Kishan Wimalawarne; Masashi Sugiyama; Ryota Tomioka (NIPS, 2014)

Discovering Emerging Topics in Social Streams via Link-Anomaly Detection. - Toshimitsu Takahashi; Ryota Tomioka; Kenji Yamanishi (IEEE Trans. Knowl. Data Eng., 2014)

Norm-Based Capacity Control in Neural Networks. - Behnam Neyshabur; Ryota Tomioka; Nathan Srebro (COLT, 2015)

Interpolating Convex and Non-Convex Tensor Decompositions via the Subspace Norm. - Qinqing Zheng; Ryota Tomioka (NIPS, 2015)

In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning. - Behnam Neyshabur; Ryota Tomioka; Nathan Srebro (ICLR (Workshop), 2015)

Jointly Learning Multiple Perceptual Similarities. - Liwen Zhang; Subhransu Maji; Ryota Tomioka (CoRR, 2015)

The algebraic combinatorial approach for low-rank matrix completion. - Franz J. Király; Louis Theran; Ryota Tomioka (J. Mach. Learn. Res., 2015)

Condition for perfect dimensionality recovery by variational Bayesian PCA. - Shinichi Nakajima; Ryota Tomioka; Masashi Sugiyama; S. Derin Babacan (J. Mach. Learn. Res., 2015)

Early detection of persistent topics in social networks. - Shota Saito; Ryota Tomioka; Kenji Yamanishi (Soc. Netw. Anal. Min., 2015)

f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization. - Sebastian Nowozin; Botond Cseke; Ryota Tomioka (NIPS, 2016)

QSGD: Randomized Quantization for Communication-Optimal Stochastic Gradient Descent. - Dan Alistarh; Jerry Li 001; Ryota Tomioka; Milan Vojnovic (CoRR, 2016)

Data-Dependent Path Normalization in Neural Networks. - Behnam Neyshabur; Ryota Tomioka; Ruslan Salakhutdinov; Nathan Srebro (ICLR (Poster), 2016)

Gaussian Attention Model and Its Application to Knowledge Base Embedding and Question Answering. - Liwen Zhang; John M. Winn; Ryota Tomioka (CoRR, 2016)

Theoretical and Experimental Analyses of Tensor-Based Regression and Classification. - Kishan Wimalawarne; Ryota Tomioka; Masashi Sugiyama (Neural Comput., 2016)

Batch Policy Gradient Methods for Improving Neural Conversation Models. - Kirthevasan Kandasamy; Yoram Bachrach; Ryota Tomioka; Daniel Tarlow; David Carter (ICLR (Poster), 2017)

QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding. - Dan Alistarh; Demjan Grubic; Jerry Li 001; Ryota Tomioka; Milan Vojnovic (NIPS, 2017)

AMPNet: Asynchronous Model-Parallel Training for Dynamic Neural Networks. - Alex Gaunt; Matthew Johnson; Maik Riechert; Daniel Tarlow; Ryota Tomioka; Dimitrios Vytiniotis; Sam Webster (CoRR, 2017)

Geometry of Optimization and Implicit Regularization in Deep Learning. - Behnam Neyshabur; Ryota Tomioka; Ruslan Salakhutdinov; Nathan Srebro (CoRR, 2017)

Multi-Level Variational Autoencoder: Learning Disentangled Representations From Grouped Observations. - Diane Bouchacourt; Ryota Tomioka; Sebastian Nowozin (AAAI, 2018)

Depth and nonlinearity induce implicit exploration for RL. - Justas Dauparas; Ryota Tomioka; Katja Hofmann (CoRR, 2018)

On Certifying Non-Uniform Bounds against Adversarial Attacks. - Chen Liu 027; Ryota Tomioka; Volkan Cevher (ICML, 2019)

Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders. - Emile Mathieu; Charline Le Lan; Chris J. Maddison; Ryota Tomioka; Yee Whye Teh (NeurIPS, 2019)

Hierarchical Representations with Poincaré Variational Auto-Encoders. - Emile Mathieu; Charline Le Lan; Chris J. Maddison; Ryota Tomioka; Yee Whye Teh (CoRR, 2019)

On Certifying Non-uniform Bound against Adversarial Attacks. - Chen Liu 027; Ryota Tomioka; Volkan Cevher (CoRR, 2019)

Conservative Uncertainty Estimation By Fitting Prior Networks. - Kamil Ciosek; Vincent Fortuin; Ryota Tomioka; Katja Hofmann; Richard E. Turner (ICLR, 2020)

On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them. - Chen Liu 027; Mathieu Salzmann; Tao Lin 004; Ryota Tomioka; Sabine Süsstrunk (NeurIPS, 2020)

Regularized Policies are Reward Robust. - Hisham Husain; Kamil Ciosek; Ryota Tomioka (AISTATS, 2021)

DistIR: An Intermediate Representation for Optimizing Distributed Neural Networks. - Keshav Santhanam; Siddharth Krishna 001; Ryota Tomioka; Andrew W. Fitzgibbon; Tim Harris 001 (EuroMLSys@EuroSys, 2021)

An Information-theoretic Approach to Distribution Shifts. - Marco Federici; Ryota Tomioka; Patrick Forré (NeurIPS, 2021)

DistIR: An Intermediate Representation and Simulator for Efficient Neural Network Distribution. - Keshav Santhanam; Siddharth Krishna 001; Ryota Tomioka; Tim Harris 001; Matei Zaharia (CoRR, 2021)

Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics. - Leon Klein; Andrew Y. K. Foong; Tor Erlend Fjelde; Bruno Mlodozeniec; Marc Brockschmidt; Sebastian Nowozin; Frank Noé; Ryota Tomioka (NeurIPS, 2023)

MatterGen: a generative model for inorganic materials design. - Claudio Zeni; Robert Pinsler; Daniel Zügner; Andrew Fowler; Matthew Horton; Xiang Fu 005; Sasha Shysheya; Jonathan Crabbé; Lixin Sun; Jake Smith; Ryota Tomioka; Tian Xie (CoRR, 2023)

Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck. - Marco Federici; Patrick Forré; Ryota Tomioka; Bastiaan S. Veeling (ICLR, 2024)