Ryota Tomioka

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 32

Top Topics

Top Venues

Publications

Marco Federici, Patrick Forré, Ryota Tomioka, Bastiaan S. Veeling
Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck. ICLR (2024)
Leon Klein, Andrew Y. K. Foong, Tor Erlend Fjelde, Bruno Mlodozeniec, Marc Brockschmidt, Sebastian Nowozin, Frank Noé, Ryota Tomioka
Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics. CoRR (2023)
Marco Federici, Patrick Forré, Ryota Tomioka, Bastiaan S. Veeling
Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck. CoRR (2023)
Leon Klein, Andrew Y. K. Foong, Tor Erlend Fjelde, Bruno Mlodozeniec, Marc Brockschmidt, Sebastian Nowozin, Frank Noé, Ryota Tomioka
Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics. NeurIPS (2023)
Claudio Zeni, Robert Pinsler, Daniel Zügner, Andrew Fowler, Matthew Horton, Xiang Fu, Sasha Shysheya, Jonathan Crabbé, Lixin Sun, Jake Smith, Ryota Tomioka, Tian Xie
MatterGen: a generative model for inorganic materials design. CoRR (2023)
Marco Federici, Ryota Tomioka, Patrick Forré
An Information-theoretic Approach to Distribution Shifts. NeurIPS (2021)
Keshav Santhanam, Siddharth Krishna, Ryota Tomioka, Tim Harris, Matei Zaharia
DistIR: An Intermediate Representation and Simulator for Efficient Neural Network Distribution. CoRR (2021)
Keshav Santhanam, Siddharth Krishna, Ryota Tomioka, Andrew W. Fitzgibbon, Tim Harris
DistIR: An Intermediate Representation for Optimizing Distributed Neural Networks. EuroMLSys@EuroSys (2021)
Marco Federici, Ryota Tomioka, Patrick Forré
An Information-theoretic Approach to Distribution Shifts. CoRR (2021)
Hisham Husain, Kamil Ciosek, Ryota Tomioka
Regularized Policies are Reward Robust. CoRR (2021)
Hisham Husain, Kamil Ciosek, Ryota Tomioka
Regularized Policies are Reward Robust. AISTATS (2021)
Chen Liu, Mathieu Salzmann, Tao Lin, Ryota Tomioka, Sabine Süsstrunk
On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them. CoRR (2020)
Chen Liu, Mathieu Salzmann, Tao Lin, Ryota Tomioka, Sabine Süsstrunk
On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them. NeurIPS (2020)
Kamil Ciosek, Vincent Fortuin, Ryota Tomioka, Katja Hofmann, Richard E. Turner
Conservative Uncertainty Estimation By Fitting Prior Networks. ICLR (2020)
Emile Mathieu, Charline Le Lan, Chris J. Maddison, Ryota Tomioka, Yee Whye Teh
Hierarchical Representations with Poincaré Variational Auto-Encoders. CoRR (2019)
Chen Liu, Ryota Tomioka, Volkan Cevher
On Certifying Non-Uniform Bounds against Adversarial Attacks. ICML (2019)
Chen Liu, Ryota Tomioka, Volkan Cevher
On Certifying Non-uniform Bound against Adversarial Attacks. CoRR (2019)
Emile Mathieu, Charline Le Lan, Chris J. Maddison, Ryota Tomioka, Yee Whye Teh
Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders. NeurIPS (2019)
Justas Dauparas, Ryota Tomioka, Katja Hofmann
Depth and nonlinearity induce implicit exploration for RL. CoRR (2018)
Diane Bouchacourt, Ryota Tomioka, Sebastian Nowozin
Multi-Level Variational Autoencoder: Learning Disentangled Representations From Grouped Observations. AAAI (2018)
Kirthevasan Kandasamy, Yoram Bachrach, Ryota Tomioka, Daniel Tarlow, David Carter
Batch Policy Gradient Methods for Improving Neural Conversation Models. CoRR (2017)
Alex Gaunt, Matthew Johnson, Maik Riechert, Daniel Tarlow, Ryota Tomioka, Dimitrios Vytiniotis, Sam Webster
AMPNet: Asynchronous Model-Parallel Training for Dynamic Neural Networks. CoRR (2017)
Diane Bouchacourt, Ryota Tomioka, Sebastian Nowozin
Multi-Level Variational Autoencoder: Learning Disentangled Representations from Grouped Observations. CoRR (2017)
Behnam Neyshabur, Ryota Tomioka, Ruslan Salakhutdinov, Nathan Srebro
Geometry of Optimization and Implicit Regularization in Deep Learning. CoRR (2017)
Dan Alistarh, Demjan Grubic, Jerry Li, Ryota Tomioka, Milan Vojnovic
QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding. NIPS (2017)
Kirthevasan Kandasamy, Yoram Bachrach, Ryota Tomioka, Daniel Tarlow, David Carter
Batch Policy Gradient Methods for Improving Neural Conversation Models. ICLR (Poster) (2017)
Dan Alistarh, Jerry Li, Ryota Tomioka, Milan Vojnovic
QSGD: Randomized Quantization for Communication-Optimal Stochastic Gradient Descent. CoRR (2016)
Kishan Wimalawarne, Ryota Tomioka, Masashi Sugiyama
Theoretical and Experimental Analyses of Tensor-Based Regression and Classification. Neural Comput. 28 (4) (2016)
Sebastian Nowozin, Botond Cseke, Ryota Tomioka
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization. NIPS (2016)
Liwen Zhang, John M. Winn, Ryota Tomioka
Gaussian Attention Model and Its Application to Knowledge Base Embedding and Question Answering. CoRR (2016)
Sebastian Nowozin, Botond Cseke, Ryota Tomioka
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization. CoRR (2016)
Behnam Neyshabur, Ryota Tomioka, Ruslan Salakhutdinov, Nathan Srebro
Data-Dependent Path Normalization in Neural Networks. ICLR (Poster) (2016)
Shota Saito, Ryota Tomioka, Kenji Yamanishi
Early detection of persistent topics in social networks. Soc. Netw. Anal. Min. 5 (1) (2015)
Qinqing Zheng, Ryota Tomioka
Interpolating Convex and Non-Convex Tensor Decompositions via the Subspace Norm. CoRR (2015)
Franz J. Király, Louis Theran, Ryota Tomioka
The algebraic combinatorial approach for low-rank matrix completion. J. Mach. Learn. Res. 16 (2015)
Behnam Neyshabur, Ryota Tomioka, Nathan Srebro
In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning. ICLR (Workshop) (2015)
Kishan Wimalawarne, Ryota Tomioka, Masashi Sugiyama
Theoretical and Experimental Analyses of Tensor-Based Regression and Classification. CoRR (2015)
Shinichi Nakajima, Ryota Tomioka, Masashi Sugiyama, S. Derin Babacan
Condition for perfect dimensionality recovery by variational Bayesian PCA. J. Mach. Learn. Res. 16 (2015)
Liwen Zhang, Subhransu Maji, Ryota Tomioka
Jointly Learning Multiple Perceptual Similarities. CoRR (2015)
Behnam Neyshabur, Ryota Tomioka, Nathan Srebro
Norm-Based Capacity Control in Neural Networks. CoRR (2015)
Qinqing Zheng, Ryota Tomioka
Interpolating Convex and Non-Convex Tensor Decompositions via the Subspace Norm. NIPS (2015)
Behnam Neyshabur, Ryota Tomioka, Nathan Srebro
Norm-Based Capacity Control in Neural Networks. COLT (2015)
Toshimitsu Takahashi, Ryota Tomioka, Kenji Yamanishi
Discovering Emerging Topics in Social Streams via Link-Anomaly Detection. IEEE Trans. Knowl. Data Eng. 26 (1) (2014)
Kishan Wimalawarne, Masashi Sugiyama, Ryota Tomioka
Multitask learning meets tensor factorization: task imputation via convex optimization. NIPS (2014)
Shota Saito, Ryota Tomioka, Kenji Yamanishi
Early detection of persistent topics in social networks. ASONAM (2014)
Shinichi Nakajima, Masashi Sugiyama, S. Derin Babacan, Ryota Tomioka
Global analytic solution of fully-observed variational Bayesian matrix factorization. J. Mach. Learn. Res. 14 (1) (2013)
Kazuyoshi Yoshii, Ryota Tomioka, Daichi Mochihashi, Masataka Goto
Beyond NMF: Time-Domain Audio Source Separation without Phase Reconstruction. ISMIR (2013)
Ryota Tomioka, Taiji Suzuki
Convex Tensor Decomposition via Structured Schatten Norm Regularization. NIPS (2013)
Zenghan Liang, Ryota Tomioka, Hiroshi Murata, Ryo Asaoka, Kenji Yamanishi
Quantitative Prediction of Glaucomatous Visual Field Loss from Few Measurements. ICDM (2013)
Koh Takeuchi, Ryota Tomioka, Katsuhiko Ishiguro, Akisato Kimura, Hiroshi Sawada
Non-negative Multiple Tensor Factorization. ICDM (2013)
Ryota Tomioka, Taiji Suzuki
Convex Tensor Decomposition via Structured Schatten Norm Regularization CoRR (2013)
Kazuyoshi Yoshii, Ryota Tomioka, Daichi Mochihashi, Masataka Goto
Infinite Positive Semidefinite Tensor Factorization for Source Separation of Mixture Signals. ICML (3) (2013)
Kohei Hayashi, Takashi Takenouchi, Ryota Tomioka, Hisashi Kashima
Self-measuring Similarity for Multi-task Gaussian Process. ICML Unsupervised and Transfer Learning (2012)
Shinichi Nakajima, Ryota Tomioka, Masashi Sugiyama, S. Derin Babacan
Perfect Dimensionality Recovery by Variational Bayesian PCA. NIPS (2012)
Franz J. Király, Ryota Tomioka
A Combinatorial Algebraic Approach for the Identifiability of Low-Rank Matrix Completion. ICML (2012)
Franz J. Király, Louis Theran, Ryota Tomioka, Takeaki Uno
The Algebraic Combinatorial Approach for Low-Rank Matrix Completion CoRR (2012)
Atsuhiro Narita, Kohei Hayashi, Ryota Tomioka, Hisashi Kashima
Tensor factorization using auxiliary information. Data Min. Knowl. Discov. 25 (2) (2012)
Ryota Tomioka, Morten Mørup
A Bayesian Analysis of the Radioactive Releases of Fukushima. AISTATS (2012)
Atsuhiro Narita, Kohei Hayashi, Ryota Tomioka, Hisashi Kashima
Tensor Factorization Using Auxiliary Information. ECML/PKDD (2) (2011)
Xu Sun, Hisashi Kashima, Ryota Tomioka, Naonori Ueda, Ping Li
A New Multi-task Learning Method for Personalized Activity Recognition. ICDM (2011)
Toshimitsu Takahashi, Ryota Tomioka, Kenji Yamanishi
Discovering Emerging Topics in Social Streams via Link Anomaly Detection CoRR (2011)
Ryota Tomioka, Taiji Suzuki, Masashi Sugiyama
Super-Linear Convergence of Dual Augmented Lagrangian Algorithm for Sparsity Regularized Estimation. J. Mach. Learn. Res. 12 (2011)
Taiji Suzuki, Ryota Tomioka
SpicyMKL: a fast algorithm for Multiple Kernel Learning with thousands of kernels. Mach. Learn. 85 (1-2) (2011)
Xu Sun, Hisashi Kashima, Ryota Tomioka, Naonori Ueda
Large Scale Real-Life Action Recognition Using Conditional Random Fields with Stochastic Training. PAKDD (2) (2011)
Toshimitsu Takahashi, Ryota Tomioka, Kenji Yamanishi
Discovering Emerging Topics in Social Streams via Link Anomaly Detection. ICDM (2011)
Ryota Tomioka, Taiji Suzuki, Kohei Hayashi, Hisashi Kashima
Statistical Performance of Convex Tensor Decomposition. NIPS (2011)
Yasuhiro Urabe, Kenji Yamanishi, Ryota Tomioka, Hiroki Iwai
Real-Time Change-Point Detection Using Sequentially Discounting Normalized Maximum Likelihood Coding. PAKDD (2) (2011)
Stefan Haufe, Ryota Tomioka, Thorsten Dickhaus, Claudia Sannelli, Benjamin Blankertz, Guido Nolte, Klaus-Robert Müller
Large-scale EEG/MEG source localization with spatial flexibility. NeuroImage 54 (2) (2011)
Stefan Haufe, Ryota Tomioka, Guido Nolte, Klaus-Robert Müller, Motoaki Kawanabe
Modeling Sparse Connectivity Between Underlying Brain Sources for EEG/MEG. IEEE Trans. Biomed. Eng. 57 (8) (2010)
Shinichi Nakajima, Masashi Sugiyama, Ryota Tomioka
Global Analytic Solution for Variational Bayesian Matrix Factorization. NIPS (2010)
Ryota Tomioka, Klaus-Robert Müller
A regularized discriminative framework for EEG analysis with application to brain-computer interface. NeuroImage 49 (1) (2010)
Ryota Tomioka, Taiji Suzuki
Regularization Strategies and Empirical Bayesian Learning for MKL. CoRR (2010)
Ryota Tomioka, Taiji Suzuki, Masashi Sugiyama, Hisashi Kashima
A Fast Augmented Lagrangian Algorithm for Learning Low-Rank Matrices. ICML (2010)
Ryota Tomioka, Masashi Sugiyama
Dual-Augmented Lagrangian Method for Efficient Sparse Reconstruction. IEEE Signal Process. Lett. 16 (12) (2009)
Ryota Tomioka, Taiji Suzuki, Masashi Sugiyama
Super-Linear Convergence of Dual Augmented-Lagrangian Algorithm for Sparsity Regularized Estimation. CoRR (2009)
Benjamin Blankertz, Ryota Tomioka, Steven Lemm, Motoaki Kawanabe, Klaus-Robert Müller
Optimizing Spatial filters for Robust EEG Single-Trial Analysis. IEEE Signal Process. Mag. 25 (1) (2008)
Benjamin Blankertz, Motoaki Kawanabe, Ryota Tomioka, Friederike U. Hohlefeld, Vadim V. Nikulin, Klaus-Robert Müller
Invariant Common Spatial Patterns: Alleviating Nonstationarities in Brain-Computer Interfacing. NIPS (2007)
Ryota Tomioka, Kazuyuki Aihara
Classifying matrices with a spectral regularization. ICML (2007)
Ryota Tomioka, Guido Dornhege, Guido Nolte, Kazuyuki Aihara, Klaus-Robert Müller
Optimizing Spectral Filters for Single Trial EEG Classification. DAGM-Symposium (2006)
Ryota Tomioka, Kazuyuki Aihara, Klaus-Robert Müller
Logistic Regression for Single Trial EEG Classification. NIPS (2006)