Ryota Tomioka

Ryota Tomioka, Kenji Yamanishi, Shota Saito, 2014, 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014).

Early detection of persistent topics in social networks

Ryota Tomioka, Kenji Yamanishi, Shota Saito, 2014, ASONAM.

Multitask learning meets tensor factorization: task imputation via convex optimization

Masashi Sugiyama, Ryota Tomioka, Kishan Wimalawarne, 2014, NIPS.

Classifying matrices with a spectral regularization

Kazuyuki Aihara, Ryota Tomioka, Ryota Tomioka, 2007, ICML '07.

Perfect Dimensionality Recovery by Variational Bayesian PCA

Shinichi Nakajima, Masashi Sugiyama, Ryota Tomioka, 2012, NIPS.

Hierarchical Representations with Poincaré Variational Auto-Encoders pdf

Yee Whye Teh, Ryota Tomioka, Emile Mathieu, 2019, ArXiv.

AMPNet: Asynchronous Model-Parallel Training for Dynamic Neural Networks pdf

Ryota Tomioka, Alexander L. Gaunt, Maik Riechert, 2017, ArXiv.

Super-Linear Convergence of Dual Augmented Lagrangian Algorithm for Sparsity Regularized Estimation

Masashi Sugiyama, Taiji Suzuki, Ryota Tomioka, 2009, J. Mach. Learn. Res..

Quantitative Prediction of Glaucomatous Visual Field Loss from Few Measurements

Ryota Tomioka, Kenji Yamanishi, Hiroshi Murata, 2013, 2013 IEEE 13th International Conference on Data Mining.

Communication-Efficient Stochastic Gradient Descent, with Applications to Neural Networks

Dan Alistarh, Ryota Tomioka, Jerry Liu, 2017, NIPS 2017.

Discovering Emerging Topics in Social Streams via Link Anomaly Detection

Ryota Tomioka, Kenji Yamanishi, Toshimitsu Takahashi, 2011, 2011 IEEE 11th International Conference on Data Mining.

A Fast Augmented Lagrangian Algorithm for Learning Low-Rank Matrices

Masashi Sugiyama, Hisashi Kashima, Taiji Suzuki, 2010, ICML.

Jointly Learning Multiple Perceptual Similarities pdf

Subhransu Maji, Ryota Tomioka, Liwen Zhang, 2015, ArXiv.

Global Analytic Solution for Variational Bayesian Matrix Factorization

Shinichi Nakajima, Masashi Sugiyama, Ryota Tomioka, 2010, NIPS.

On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them pdf

Tao Lin, Ryota Tomioka, Mathieu Salzmann, 2020, NeurIPS.

QSGD: Randomized Quantization for Communication-Optimal Stochastic Gradient Descent pdf

Dan Alistarh, Jerry Li, Ryota Tomioka, 2016, ArXiv.

Theoretical and Experimental Analyses of Tensor-Based Regression and Classification

Masashi Sugiyama, Ryota Tomioka, Kishan Wimalawarne, 2015, Neural Computation.

Condition for perfect dimensionality recovery by variational Bayesian PCA

Shinichi Nakajima, Masashi Sugiyama, Ryota Tomioka, 2015, J. Mach. Learn. Res..

Large Scale Real-Life Action Recognition Using Conditional Random Fields with Stochastic Training

Xu Sun, Hisashi Kashima, Naonori Ueda, 2011, PAKDD.

Self-measuring Similarity for Multi-task Gaussian Process

Hisashi Kashima, Ryota Tomioka, Kohei Hayashi, 2011, ICML Unsupervised and Transfer Learning.

Interpolating Convex and Non-Convex Tensor Decompositions via the Subspace Norm

Ryota Tomioka, Qinqing Zheng, Ryota Tomioka, 2015, NIPS.

Conservative Uncertainty Estimation By Fitting Prior Networks

Richard E. Turner, Ryota Tomioka, Katja Hofmann, 2020, ICLR.

Dual-Augmented Lagrangian Method for Efficient Sparse Reconstruction

Masashi Sugiyama, Ryota Tomioka, Ryota Tomioka, 2009, IEEE Signal Processing Letters.

Quantized stochastic gradient descent: communication versus convergence

Dan Alistarh, Jerry Li, Ryota Tomioka, 2016 .

Super-Linear Convergence of Dual Augmented Lagrangian Algorithm for Sparse Learning

Masashi Sugiyama, Taiji Suzuki, Ryota Tomioka, 2009 .

The algebraic combinatorial approach for low-rank matrix completion

Franz J. Király, Ryota Tomioka, Louis Theran, 2012, J. Mach. Learn. Res..

Discovering Emerging Topics in Social Streams via Link-Anomaly Detection

Ryota Tomioka, Kenji Yamanishi, Toshimitsu Takahashi, 2014, IEEE Transactions on Knowledge and Data Engineering.

Geometry of Optimization and Implicit Regularization in Deep Learning pdf

Ruslan Salakhutdinov, Ryota Tomioka, Nathan Srebro, 2017, ArXiv.

Tensor Factorization Using Auxiliary Information

Hisashi Kashima, Ryota Tomioka, Kohei Hayashi, 2011, ECML/PKDD.

Depth and nonlinearity induce implicit exploration for RL pdf

Katja Hofmann, Ryota Tomioka, Justas Dauparas, 2018, ArXiv.

Gaussian Attention Model and Its Application to Knowledge Base Embedding and Question Answering pdf

Ryota Tomioka, John M. Winn, Liwen Zhang, 2016, ArXiv.

Statistical Performance of Convex Tensor Decomposition

Hisashi Kashima, Taiji Suzuki, Ryota Tomioka, 2011, NIPS.

MATHEMATICAL ENGINEERING TECHNICAL REPORTS Spectrally weighted Common Spatial Pattern algorithm for single trial EEG classification

Benjamin Blankertz, Guido Nolte, Ryota Tomioka, 2006 .

A regularized discriminative framework for EEG analysis with application to brain–computer interface

Klaus-Robert Müller, Ryota Tomioka, K. Müller, 2010, NeuroImage.

Augmented Lagrangian Methods for Learning, Selecting, and Combining Features

Masashi Sugiyama, Taiji Suzuki, Ryota Tomioka, 2011 .

Real-Time Change-Point Detection Using Sequentially Discounting Normalized Maximum Likelihood Coding

Ryota Tomioka, Kenji Yamanishi, Hiroki Iwai, 2011, PAKDD.

Batch Policy Gradient Methods for Improving Neural Conversation Models pdf

Kirthevasan Kandasamy, David Carter, Ryota Tomioka, 2017, ICLR.

A Combinatorial Algebraic Approach for the Identifiability of Low-Rank Matrix Completion

Franz J. Király, Ryota Tomioka, Ryota Tomioka, 2012, ICML.

On Certifying Non-uniform Bound against Adversarial Attacks pdf

Volkan Cevher, Ryota Tomioka, Chen Liu, 2019, ICML.

Global analytic solution of fully-observed variational Bayesian matrix factorization

Shinichi Nakajima, Masashi Sugiyama, Ryota Tomioka, 2013, J. Mach. Learn. Res..

Infinite Positive Semidefinite Tensor Factorization for Source Separation of Mixture Signals

Masataka Goto, Kazuyoshi Yoshii, Ryota Tomioka, 2013, ICML.

Norm-Based Capacity Control in Neural Networks

Ryota Tomioka, Nathan Srebro, Behnam Neyshabur, 2015, COLT.

Optimizing Spectral Filters for Single Trial EEG Classification

Kazuyuki Aihara, Klaus-Robert Müller, Guido Nolte, 2006, DAGM-Symposium.

A New Multi-task Learning Method for Personalized Activity Recognition

Xu Sun, Hisashi Kashima, Naonori Ueda, 2011, 2011 IEEE 11th International Conference on Data Mining.

Tensor factorization using auxiliary information

Hisashi Kashima, Ryota Tomioka, Kohei Hayashi, 2011, Data Mining and Knowledge Discovery.

Adapting Spatial Filter Methods for Nonstationary BCIs

Kazuyuki Aihara, Benjamin Blankertz, Ryota Tomioka, 2006 .

SpicyMKL: a fast algorithm for Multiple Kernel Learning with thousands of kernels

Taiji Suzuki, Ryota Tomioka, Ryota Tomioka, 2011, Machine Learning.

Convex Tensor Decomposition via Structured Schatten Norm Regularization

Taiji Suzuki, Ryota Tomioka, Ryota Tomioka, 2013, NIPS.

DistIR: An Intermediate Representation for Optimizing Distributed Neural Networks

Ryota Tomioka, Keshav Santhanam, Siddharth Krishna, 2021, EuroMLSys@EuroSys.

DistIR: An Intermediate Representation and Simulator for Efficient Neural Network Distribution pdf

Ryota Tomioka, Keshav Santhanam, Matei Zaharia, 2021, ArXiv.

Jointly Learning Multiple Measures of Similarities from Triplet Comparisons

Subhransu Maji, Ryota Tomioka, Liwen Zhang, 2015 .

Multivariate analysis of noise in genetic regulatory networks.

Kazuyuki Aihara, Ryota Tomioka, Ryota Tomioka, 2004, Journal of theoretical biology.