NIPS Proceedings
^{β}
Books
Masashi Sugiyama
30 Papers
Binary Classification from Positive-Confidence Data
(2018)
Continuous-time Value Function Approximation in Reproducing Kernel Hilbert Spaces
(2018)
Co-teaching: Robust training of deep neural networks with extremely noisy labels
(2018)
Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks
(2018)
Masking: A New Perspective of Noisy Supervision
(2018)
Uplift Modeling from Separate Labels
(2018)
Expectation Propagation for t-Exponential Family Using q-Algebra
(2017)
Generative Local Metric Learning for Kernel Regression
(2017)
Learning from Complementary Labels
(2017)
Positive-Unlabeled Learning with Non-Negative Risk Estimator
(2017)
Theoretical Comparisons of Positive-Unlabeled Learning against Positive-Negative Learning
(2016)
Analysis of Learning from Positive and Unlabeled Data
(2014)
Analysis of Variational Bayesian Latent Dirichlet Allocation: Weaker Sparsity Than MAP
(2014)
Multitask learning meets tensor factorization: task imputation via convex optimization
(2014)
Global Solver and Its Efficient Approximation for Variational Bayesian Low-rank Subspace Clustering
(2013)
Parametric Task Learning
(2013)
Density-Difference Estimation
(2012)
Perfect Dimensionality Recovery by Variational Bayesian PCA
(2012)
Analysis and Improvement of Policy Gradient Estimation
(2011)
Global Solution of Fully-Observed Variational Bayesian Matrix Factorization is Column-Wise Independent
(2011)
Relative Density-Ratio Estimation for Robust Distribution Comparison
(2011)
Target Neighbor Consistent Feature Weighting for Nearest Neighbor Classification
(2011)
Global Analytic Solution for Variational Bayesian Matrix Factorization
(2010)
Efficient Direct Density Ratio Estimation for Non-stationarity Adaptation and Outlier Detection
(2008)
Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation
(2007)
Multi-Task Learning via Conic Programming
(2007)
Mixture Regression for Covariate Shift
(2006)
Active Learning for Misspecified Models
(2005)
Non-Gaussian Component Analysis: a Semi-parametric Framework for Linear Dimension Reduction
(2005)
Training Data Selection for Optimal Generalization in Trigonometric Polynomial Networks
(1999)
2 Books
Advances in Neural Information Processing Systems 29
(2016)
Advances in Neural Information Processing Systems 28
(2015)