Masashi Sugiyama

	2009
62		Masashi Sugiyama: Density Ratio Estimation: A New Versatile Tool for Machine Learning. ACML 2009: 6-9
61		Hirotaka Hachiya, Jan Peters, Masashi Sugiyama: Efficient Sample Reuse in EM-Based Policy Search. ECML/PKDD (1) 2009: 469-484
60		Taiji Suzuki, Masashi Sugiyama: Estimating Squared-Loss Mutual Information for Independent Component Analysis. ICA 2009: 130-137
59		Takayuki Akiyama, Hirotaka Hachiya, Masashi Sugiyama: Active Policy Iteration: Efficient Exploration through Active Learning for Value Function Approximation in Reinforcement Learning. IJCAI 2009: 980-985
58		Shinichi Nakajima, Masashi Sugiyama: Analysis of Variational Bayesian Matrix Factorization. PAKDD 2009: 314-326
57		Hisashi Kashima, Tsuyoshi Kato, Yoshihiro Yamanishi, Masashi Sugiyama, Koji Tsuda: Link Propagation: A Fast Semi-supervised Learning Algorithm for Link Prediction. SDM 2009: 1099-1110
56		Yoshinobu Kawahara, Masashi Sugiyama: Change-Point Detection in Time-Series Data by Direct Density-Ratio Estimation. SDM 2009: 389-400
55		Taiji Suzuki, Masashi Sugiyama, Takafumi Kanamori, Jun Sese: Mutual information estimation reveals global associations between stimuli and biological processes. BMC Bioinformatics 10(S-1): (2009)
54		Takeaki Uno, Masashi Sugiyama, Koji Tsuda: Efficient Construction of Neighborhood Graphs by the Multiple Sorting Method CoRR abs/0904.3151: (2009)
53		Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama: Robust Label Propagation on Multiple Networks. IEEE Transactions on Neural Networks 20(1): 35-44 (2009)
52		Masashi Sugiyama: On Computational Issues of Semi-Supervised Local Fisher Discriminant Analysis. IEICE Transactions 92-D(5): 1204-1208 (2009)
51		Hisashi Kashima, Tsuyoshi Idé, Tsuyoshi Kato, Masashi Sugiyama: Recent Advances and Trends in Large-Scale Kernel Methods. IEICE Transactions 92-D(7): 1338-1353 (2009)
50		Liwei Wang, Masashi Sugiyama, Cheng Yang, Kohei Hatano, Jufu Feng: Theory and Algorithm for Learning with Dissimilarity Functions. Neural Computation 21(5): 1459-1484 (2009)
	2008
49		Hirotaka Hachiya, Takayuki Akiyama, Masashi Sugiyama, Jan Peters: Adaptive Importance Sampling with Automatic Model Selection in Value Function Approximation. AAAI 2008: 1351-1356
48		Liwei Wang, Masashi Sugiyama, Cheng Yang, Zhi-Hua Zhou, Jufu Feng: On the Margin Explanation of Boosting Algorithms. COLT 2008: 479-490
47		Masashi Sugiyama, Shinichi Nakajima: Pool-Based Agnostic Experiment Design in Linear Regression. ECML/PKDD (2) 2008: 406-422
46		Shohei Hido, Yuta Tsuboi, Hisashi Kashima, Masashi Sugiyama, Takafumi Kanamori: Inlier-Based Outlier Detection via Direct Density Ratio Estimation. ICDM 2008: 223-232
45		Akiko Takeda, Masashi Sugiyama: nu-support vector machine as conditional value-at-risk minimization. ICML 2008: 1056-1063
44		Neil Rubens, Vera Sheinman, Takenobu Tokunaga, Masashi Sugiyama: Order Retrieval. LKR 2008: 310-317
43		Takafumi Kanamori, Shohei Hido, Masashi Sugiyama: Efficient Direct Density Ratio Estimation for Non-stationarity Adaptation and Outlier Detection. NIPS 2008: 809-816
42		Masashi Sugiyama, Tsuyoshi Idé, Shinichi Nakajima, Jun Sese: Semi-Supervised Local Fisher Discriminant Analysis for Dimensionality Reduction. PAKDD 2008: 333-344
41		Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Steffen Bickel, Masashi Sugiyama: Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation. SDM 2008: 443-454
40		Masashi Sugiyama, Neil Rubens: Active Learning with Model Selection in Linear Regression. SDM 2008: 518-529
39		Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama: Integration of Multiple Networks for Robust Label Propagation. SDM 2008: 716-726
38		Masashi Sugiyama, Hirotaka Hachiya, Christopher Towell, Sethu Vijayakumar: Geodesic Gaussian kernels for value function approximation. Auton. Robots 25(3): 287-304 (2008)
37		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)
36		Masashi Sugiyama, Neil Rubens: A batch ensemble approach to active learning with model selection. Neural Networks 21(9): 1278-1286 (2008)
	2007
35		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
34		Masashi Sugiyama, Hirotaka Hachiya, Christopher Towell, Sethu Vijayakumar: Value Function Approximation on Non-Linear Manifolds for Robot Motor Control. ICRA 2007: 1733-1740
33		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
32		Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama, Kiyoshi Asai: Multi-Task Learning via Conic Programming. NIPS 2007
31		Neil Rubens, Masashi Sugiyama: Influence-based collaborative active learning. RecSys 2007: 145-148
30		Shun Gokita, Masashi Sugiyama, Keisuke Sakurai: Analytic Optimization of Adaptive Ridge Parameters Based on Regularized Subspace Information Criterion. IEICE Transactions 90-A(11): 2584-2592 (2007)
29		Masashi Sugiyama: Generalization Error Estimation for Non-linear Learning Methods. IEICE Transactions 90-A(7): 1496-1499 (2007)
28		Yasushi Hidaka, Masashi Sugiyama: A New Meta-Criterion for Regularized Subspace Information Criterion. IEICE Transactions 90-D(11): 1779-1786 (2007)
	2006
27		Masashi Sugiyama, Benjamin Blankertz, Matthias Krauledat, Guido Dornhege, Klaus-Robert Müller: Importance-Weighted Cross-Validation for Covariate Shift. DAGM-Symposium 2006: 354-363
26		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
25		Masashi Sugiyama: Local Fisher discriminant analysis for supervised dimensionality reduction. ICML 2006: 905-912
24		Amos J. Storkey, Masashi Sugiyama: Mixture Regression for Covariate Shift. NIPS 2006: 1337-1344
23		Akira Tanaka, Masashi Sugiyama, Hideyuki Imai, Mineichi Kudo, Masaaki Miyakoshi: Model Selection Using a Class of Kernels with an Invariant Metric. SSPR/SPR 2006: 862-870
22		Masashi Sugiyama, Keisuke Sakurai: Analytic Optimization of Shrinkage Parameters Based on Regularized Subspace Information Criterion. IEICE Transactions 89-A(8): 2216-2225 (2006)
21		Masashi Sugiyama, Hidemitsu Ogawa: Constructing Kernel Functions for Binary Regression. IEICE Transactions 89-D(7): 2243-2249 (2006)
20		Masashi Sugiyama: Active Learning in Approximately Linear Regression Based on Conditional Expectation of Generalization Error. Journal of Machine Learning Research 7: 141-166 (2006)
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		Masashi Sugiyama, Klaus-Robert Müller: Model Selection Under Covariate Shift. ICANN (2) 2005: 235-240
17		Masashi Sugiyama: Active Learning for Misspecified Models. NIPS 2005
16		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
	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		Masashi Sugiyama: Estimating the error at given test input points for linear regression. Neural Networks and Computational Intelligence 2004: 113-118
13		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)
	2002
12		Masashi Sugiyama, Klaus-Robert Müller: Selecting Ridge Parameters in Infinite Dimensional Hypothesis Spaces. ICANN 2002: 528-534
11		Masashi Sugiyama, Klaus-Robert Müller: The Subspace Information Criterion for Infinite Dimensional Hypothesis Spaces. Journal of Machine Learning Research 3: 323-359 (2002)
10		Masashi Sugiyama, Hidemitsu Ogawa: Theoretical and Experimental Evaluation of the Subspace Information Criterion. Machine Learning 48(1-3): 25-50 (2002)
9		Masashi Sugiyama, Hidemitsu Ogawa: Optimal design of regularization term and regularization parameter by subspace information criterion. Neural Networks 15(3): 349-361 (2002)
8		Masashi Sugiyama, Hidemitsu Ogawa: A unified method for optimizing linear image restoration filters. Signal Processing 82(11): 1773-1787 (2002)
	2001
7		Masashi Sugiyama, Hidemitsu Ogawa: Incremental Active Learning for Optimal Generalization. Neural Computation 12(12): 2909-2940 (2001)
6		Masashi Sugiyama, Hidemitsu Ogawa: Subspace Information Criterion for Model Selection. Neural Computation 13(8): 1863-1889 (2001)
5		Masashi Sugiyama, Hidemitsu Ogawa: Incremental projection learning for optimal generalization. Neural Networks 14(1): 53-66 (2001)
4		Masashi Sugiyama, Hidemitsu Ogawa: Properties of incremental projection learning. Neural Networks 14(1): 67-78 (2001)
	2000
3		Masashi Sugiyama, Hidemitsu Ogawa: A new information criterion for the selection of subspace models. ESANN 2000: 69-74
2		Masashi Sugiyama, Hidemitsu Ogawa: Incremental Active Learning with Bias Reduction. IJCNN (1) 2000: 15-20
	1999
1		Masashi Sugiyama, Hidemitsu Ogawa: Training Data Selection for Optimal Generalization in Trigonometric Polynomial Networks. NIPS 1999: 624-630

Coauthor Index

1	Takayuki Akiyama	[49] [59]
2	Kiyoshi Asai	[32]
3	Steffen Bickel	[41]
4	Gilles Blanchard	[16] [19] [26] [37]
5	Benjamin Blankertz	[27]
6	Paul Von Bünau	[33]
7	Guido Dornhege	[27]
8	Jufu Feng	[48] [50]
9	Shun Gokita	[30]
10	Hirotaka Hachiya	[34] [38] [49] [59] [61]
11	Kohei Hatano	[50]
12	Yasushi Hidaka	[28]
13	Shohei Hido	[41] [43] [46]
14	Tsuyoshi Idé	[42] [51]
15	Hideyuki Imai	[23]
16	Takafumi Kanamori	[43] [46] [55]
17	Hisashi Kashima	[32] [33] [39] [41] [46] [51] [53] [57]
18	Tsuyoshi Kato	[32] [39] [51] [53] [57]
19	Yoshinobu Kawahara	[56]
20	Motoaki Kawanabe	[13] [15] [16] [19] [26] [33] [35] [37]
21	Matthias Krauledat	[27]
22	Mineichi Kudo	[23]
23	Masaaki Miyakoshi	[23]
24	Klaus-Robert Müller	[11] [12] [13] [15] [16] [18] [19] [26] [27] [35] [37]
25	Shinichi Nakajima	[33] [42] [47] [58]
26	Hidemitsu Ogawa	[1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [21]
27	Jan Peters	[49] [61]
28	Neil Rubens	[31] [36] [40] [44]
29	Keisuke Sakurai	[22] [30]
30	Jun Sese	[42] [55]
31	Vera Sheinman	[44]
32	Vladimir Spokoiny	[16] [19] [26]
33	Amos J. Storkey	[24]
34	Taiji Suzuki	[55] [60]
35	Akiko Takeda	[45]
36	Akira Tanaka	[23]
37	Takenobu Tokunaga	[44]
38	Christopher Towell	[34] [38]
39	Yuta Tsuboi	[41] [46]
40	Koji Tsuda	[54] [57]
41	Takeaki Uno	[54]
42	Sethu Vijayakumar	[34] [38]
43	Liwei Wang	[48] [50]
44	Sumio Watanabe	[35]
45	Yoshihiro Yamanishi	[57]
46	Keisuke Yamazaki	[35]
47	Cheng Yang	[48] [50]
48	Zhi-Hua Zhou	[48]

Colors in the list of coauthors