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All publications by Masashi Sugiyama
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Convex Formulation for Learning from Positive and Unlabeled Data
Marthinus D. Plessis, Gang Niu and Masashi Sugiyama
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Outlier Path: A Homotopy Algorithm for Robust SVM
Shinya Suzumura, Kohei Ogawa, Masashi Sugiyama and Ichiro Takeuchi
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Transductive Learning with Multi-class Volume Approximation
Gang Niu, Bo Dai, Christoffel D. Plessis and Masashi Sugiyama
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Multitask learning meets tensor factorization: task imputation via convex optimization
Kishan Wimalawarne, Masashi Sugiyama and Ryota Tomioka
Advances in Neural Information Processing Systems 27, 2014


Analysis of Variational Bayesian Latent Dirichlet Allocation: Weaker Sparsity Than MAP
Shinichi Nakajima, Issei Sato, Masashi Sugiyama, Kazuho Watanabe and Hiroko Kobayashi
Advances in Neural Information Processing Systems 27, 2014


Analysis of Learning from Positive and Unlabeled Data
Marthinus Plessis, Gang Niu and Masashi Sugiyama
Advances in Neural Information Processing Systems 27, 2014


Infinitesimal Annealing for Training Semi-Supervised Support Vector Machines
Kohei Ogawa, Motoki Imamura, Ichiro Takeuchi and Masashi Sugiyama
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


Squared-loss Mutual Information Regularization: A Novel Information-theoretic Approach to Semi-supervised Learning
Gang Niu, Wittawat Jitkrittum, Bo Dai, Hirotaka Hachiya and Masashi Sugiyama
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


Parametric Task Learning
Ichiro Takeuchi, Tatsuya Hongo, Masashi Sugiyama and Shinichi Nakajima
Advances in Neural Information Processing Systems 26, 2013


Global Solver and Its Efficient Approximation for Variational Bayesian Low-rank Subspace Clustering
Shinichi Nakajima, Akiko Takeda, S. D. Babacan, Masashi Sugiyama and Ichiro Takeuchi
Advances in Neural Information Processing Systems 26, 2013


Perfect Dimensionality Recovery by Variational Bayesian PCA
Shinichi Nakajima, Ryota Tomioka, Masashi Sugiyama and S. D. Babacan
Advances in Neural Information Processing Systems 25, 2012


Density-Difference Estimation
Masashi Sugiyama, Takafumi Kanamori, Taiji Suzuki, Marthinus D. Plessis, Song Liu and Ichiro Takeuchi
Advances in Neural Information Processing Systems 25, 2012


Artist Agent: A Reinforcement Learning Approach to Automatic Stroke Generation in Oriental Ink Painting
Ning Xie, Hirotaka Hachiya and Masashi Sugiyama
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Information-theoretic Semi-supervised Metric Learning via Entropy Regularization
Gang Niu, Bo Dai, Makoto Yamada and Masashi Sugiyama
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Semi-Supervised Learning of Class Balance under Class-Prior Change by Distribution Matching
Marthinus D. Plessis and Masashi Sugiyama
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Fast Learning Rate of Multiple Kernel Learning: Trade-Off between Sparsity and Smoothness
Taiji Suzuki and Masashi Sugiyama
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS-12), 2012


Relative Density-Ratio Estimation for Robust Distribution Comparison
Makoto Yamada, Taiji Suzuki, Takafumi Kanamori, Hirotaka Hachiya and Masashi Sugiyama
Advances in Neural Information Processing Systems 24, 2011


Target Neighbor Consistent Feature Weighting for Nearest Neighbor Classification
Ichiro Takeuchi and Masashi Sugiyama
Advances in Neural Information Processing Systems 24, 2011


Analysis and Improvement of Policy Gradient Estimation
Tingting Zhao, Hirotaka Hachiya, Gang Niu and Masashi Sugiyama
Advances in Neural Information Processing Systems 24, 2011


Global Solution of Fully-Observed Variational Bayesian Matrix Factorization is Column-Wise Independent
Shinichi Nakajima, Masashi Sugiyama and S. D. Babacan
Advances in Neural Information Processing Systems 24, 2011


On Information-Maximization Clustering: Tuning Parameter Selection and Analytic Solution
Masashi Sugiyama, Makoto Yamada, Manabu Kimura and Hirotaka Hachiya
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


On Bayesian PCA: Automatic Dimensionality Selection and Analytic Solution
Shinichi Nakajima, Masashi Sugiyama and Derin Babacan
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Cross-Domain Object Matching with Model Selection
Makoto Yamada and Masashi Sugiyama
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


Maximum Volume Clustering
Gang Niu, Bo Dai, Lin Shang and Masashi Sugiyama
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


A Fast Augmented Lagrangian Algorithm for Learning Low-Rank Matrices
Ryota Tomioka, Taiji Suzuki, Masashi Sugiyama and Hisashi Kashima
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Implicit Regularization in Variational Bayesian Matrix Factorization
Shinichi Nakajima and Masashi Sugiyama
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Nonparametric Return Distribution Approximation for Reinforcement Learning
Tetsuro Morimura, Masashi Sugiyama, Hisashi Kashima, Hirotaka Hachiya and Toshiyuki Tanaka
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Global Analytic Solution for Variational Bayesian Matrix Factorization
Shinichi Nakajima, Masashi Sugiyama and Ryota Tomioka
Advances in Neural Information Processing Systems 23, 2010


Sufficient Dimension Reduction via Squared-loss Mutual Information Estimation
Taiji Suzuki and Masashi Sugiyama
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Conditional Density Estimation via Least-Squares Density Ratio Estimation
Masashi Sugiyama, Ichiro Takeuchi, Taiji Suzuki, Takafumi Kanamori, Hirotaka Hachiya and Daisuke Okanohara
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


A Least-squares Approach to Direct Importance Estimation
Takafumi Kanamori, Shohei Hido and Masashi Sugiyama
Journal of Machine Learning Research, 2009


Lanczos Approximations for the Speedup of Kernel Partial Least Squares Regression
Nicole Krämer, Masashi Sugiyama and Mikio L. Braun
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS-09), 2009


{\it nu}-support vector machine as conditional value-at-risk minimization
Akiko Takeda and Masashi Sugiyama
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


Efficient Direct Density Ratio Estimation for Non-stationarity Adaptation and Outlier Detection
Takafumi Kanamori, Shohei Hido and Masashi Sugiyama
Advances in Neural Information Processing Systems 21, 2008


Asymptotic Bayesian generalization error when training and test distributions are different
Keisuke Yamazaki, Motoaki Kawanabe, Sumio Watanabe, Masashi Sugiyama and Klaus-robert Müller
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Covariate Shift Adaptation by Importance Weighted Cross Validation
Masashi Sugiyama, Matthias Krauledat and Klaus-robert Müller
Journal of Machine Learning Research, 2007


Dimensionality Reduction of Multimodal Labeled Data by Local Fisher Discriminant Analysis
Masashi Sugiyama
Journal of Machine Learning Research, 2007


Multi-Task Learning via Conic Programming
Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama and Kiyoshi Asai
Advances in Neural Information Processing Systems 20, 2007


Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation
Masashi Sugiyama, Shinichi Nakajima, Hisashi Kashima, Paul V. Buenau and Motoaki Kawanabe
Advances in Neural Information Processing Systems 20, 2007


Local Fisher discriminant analysis for supervised dimensionality reduction
Masashi Sugiyama
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006


Active Learning in Approximately Linear Regression Based on Conditional Expectation of Generalization Error
Masashi Sugiyama
Journal of Machine Learning Research, 2006


Mixture Regression for Covariate Shift
Masashi Sugiyama and Amos J. Storkey
Advances in Neural Information Processing Systems 19, 2006


In Search of Non-Gaussian Components of a High-Dimensional Distribution
Gilles Blanchard, Motoaki Kawanabe, Masashi Sugiyama, Vladimir Spokoiny and Klaus-robert Müller
Journal of Machine Learning Research, 2006


Non-Gaussian Component Analysis: a Semi-parametric Framework for Linear Dimension Reduction
Gilles Blanchard, Masashi Sugiyama, Motoaki Kawanabe, Vladimir Spokoiny and Klaus-robert Müller
Advances in Neural Information Processing Systems 18, 2005


Active Learning for Misspecified Models
Masashi Sugiyama
Advances in Neural Information Processing Systems 18, 2005


The Subspace Information Criterion for Infinite Dimensional Hypothesis Spaces
Masashi Sugiyama and Klaus-robert Müller
Journal of Machine Learning Research, 2002