| 2009 | ||
|---|---|---|
| 33 | Motoaki Kawanabe, Shinichi Nakajima, Alexander Binder: A procedure of adaptive kernel combination with kernel-target alignment for object classification. CIVR 2009 | |
| 32 | Tsuyoshi Ueno, Shin-ichi Maeda, Motoaki Kawanabe, Shin Ishii: Optimal Online Learning Procedures for Model-Free Policy Evaluation. ECML/PKDD (2) 2009: 473-488 | |
| 31 | Motoaki Kawanabe, Carmen Vidaurre, Benjamin Blankertz, Klaus-Robert Müller: A Maxmin Approach to Optimize Spatial Filters for EEG Single-Trial Classification. IWANN (1) 2009: 674-682 | |
| 2008 | ||
| 30 | Tsuyoshi Ueno, Motoaki Kawanabe, Takeshi Mori, Shin-ichi Maeda, Shin Ishii: A semiparametric statistical approach to model-free policy evaluation. ICML 2008: 1072-1079 | |
| 29 | Masashi Sugiyama, Motoaki Kawanabe, Gilles Blanchard, Klaus-Robert Müller: Approximating the Best Linear Unbiased Estimator of Non-Gaussian Signals with Gaussian Noise. IEICE Transactions 91-D(5): 1577-1580 (2008) | |
| 2007 | ||
| 28 | Fabian J. Theis, Motoaki Kawanabe: Colored Subspace Analysis. ICA 2007: 121-128 | |
| 27 | Keisuke Yamazaki, Motoaki Kawanabe, Sumio Watanabe, Masashi Sugiyama, Klaus-Robert Müller: Asymptotic Bayesian generalization error when training and test distributions are different. ICML 2007: 1079-1086 | |
| 26 | Masashi Sugiyama, Shinichi Nakajima, Hisashi Kashima, Paul Von Bünau, Motoaki Kawanabe: Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation. NIPS 2007 | |
| 25 | Shigeyuki Oba, Motoaki Kawanabe, Klaus-Robert Müller, Shin Ishii: Heterogeneous Component Analysis. NIPS 2007 | |
| 24 | Benjamin Blankertz, Motoaki Kawanabe, Ryota Tomioka, Friederike Hohlefeld, Vadim V. Nikulin, Klaus-Robert Müller: Invariant Common Spatial Patterns: Alleviating Nonstationarities in Brain-Computer Interfacing. NIPS 2007 | |
| 23 | Motoaki Kawanabe, Fabian J. Theis: Joint low-rank approximation for extracting non-Gaussian subspaces. Signal Processing 87(8): 1890-1903 (2007) | |
| 2006 | ||
| 22 | Motoaki Kawanabe, Gilles Blanchard, Masashi Sugiyama, Vladimir Spokoiny, Klaus-Robert Müller: A Novel Dimension Reduction Procedure for Searching Non-Gaussian Subspaces. ICA 2006: 149-156 | |
| 21 | Motoaki Kawanabe, Fabian J. Theis: Estimating Non-Gaussian Subspaces by Characteristic Functions. ICA 2006: 157-164 | |
| 20 | Fabian J. Theis, Motoaki Kawanabe: Uniqueness of Non-Gaussian Subspace Analysis. ICA 2006: 917-925 | |
| 19 | Gilles Blanchard, Motoaki Kawanabe, Masashi Sugiyama, Vladimir Spokoiny, Klaus-Robert Müller: In Search of Non-Gaussian Components of a High-Dimensional Distribution. Journal of Machine Learning Research 7: 247-282 (2006) | |
| 2005 | ||
| 18 | Motoaki Kawanabe: Linear Dimension Reduction Based on the Fourth-Order Cumulant Tensor. ICANN (2) 2005: 151-156 | |
| 17 | Gilles Blanchard, Masashi Sugiyama, Motoaki Kawanabe, Vladimir Spokoiny, Klaus-Robert Müller: Non-Gaussian Component Analysis: a Semi-parametric Framework for Linear Dimension Reduction. NIPS 2005 | |
| 16 | Motoaki Kawanabe, Klaus-Robert Müller: Estimating Functions for Blind Separation When Sources Have Variance Dependencies. Journal of Machine Learning Research 6: 453-482 (2005) | |
| 2004 | ||
| 15 | Masashi Sugiyama, Motoaki Kawanabe, Klaus-Robert Müller: Regularizing generalization error estimators: a novel approach to robust model selection. ESANN 2004: 163-168 | |
| 14 | Motoaki Kawanabe, Klaus-Robert Müller: Estimating Functions for Blind Separation when Sources Have Variance-Dependencies. ICA 2004: 136-143 | |
| 13 | Koji Tsuda, Shotaro Akaho, Motoaki Kawanabe, Klaus-Robert Müller: Asymptotic Properties of the Fisher Kernel. Neural Computation 16(1): 115-137 (2004) | |
| 12 | Masashi Sugiyama, Motoaki Kawanabe, Klaus-Robert Müller: Trading Variance Reduction with Unbiasedness: The Regularized Subspace Information Criterion for Robust Model Selection in Kernel Regression. Neural Computation 16(5): 1077-1104 (2004) | |
| 2003 | ||
| 11 | Volker Roth, Julian Laub, Motoaki Kawanabe, Joachim M. Buhmann: Optimal Cluster Preserving Embedding of Nonmetric Proximity Data. IEEE Trans. Pattern Anal. Mach. Intell. 25(12): 1540-1551 (2003) | |
| 10 | Andreas Ziehe, Motoaki Kawanabe, Stefan Harmeling, Klaus-Robert Müller: Blind Separation of Post-nonlinear Mixtures using Linearizing Transformations and Temporal Decorrelation. Journal of Machine Learning Research 4: 1319-1338 (2003) | |
| 9 | Stefan Harmeling, Andreas Ziehe, Motoaki Kawanabe, Klaus-Robert Müller: Kernel-Based Nonlinear Blind Source Separation. Neural Computation 15(5): 1089-1124 (2003) | |
| 2002 | ||
| 8 | Koji Tsuda, Motoaki Kawanabe: The Leave-One-Out Kernel. ICANN 2002: 727-732 | |
| 7 | Koji Tsuda, Motoaki Kawanabe, Klaus-Robert Müller: Clustering with the Fisher Score. NIPS 2002: 729-736 | |
| 6 | Koji Tsuda, Motoaki Kawanabe, Gunnar Rätsch, Sören Sonnenburg, Klaus-Robert Müller: A New Discriminative Kernel from Probabilistic Models. Neural Computation 14(10): 2397-2414 (2002) | |
| 5 | Noboru Murata, Motoaki Kawanabe, Andreas Ziehe, Klaus-Robert Müller, Shun-ichi Amari: On-line learning in changing environments with applications in supervised and unsupervised learning. Neural Networks 15(4-6): 743-760 (2002) | |
| 2001 | ||
| 4 | Frank C. Meinecke, Andreas Ziehe, Motoaki Kawanabe, Klaus-Robert Müller: Estimating the Reliability of ICA Projections. NIPS 2001: 1181-1188 | |
| 3 | Stefan Harmeling, Alexander Ziehe, Motoaki Kawanabe, Klaus-Robert Müller: Kernel Feature Spaces and Nonlinear Blind Souce Separation. NIPS 2001: 761-768 | |
| 2 | Koji Tsuda, Motoaki Kawanabe, Gunnar Rätsch, Sören Sonnenburg, Klaus-Robert Müller: A New Discriminative Kernel From Probabilistic Models. NIPS 2001: 977-984 | |
| 1994 | ||
| 1 | Motoaki Kawanabe, Shun-ichi Amari: Estimation of Network Parameters in Semiparametric Stochastic Perceptron. Neural Computation 6(6): 1244-1261 (1994) | |