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ORCIDTakashi Takenouchi
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2020 – today
- 2022
[j21]Akira Tanimoto
, So Yamada, Takashi Takenouchi, Masashi Sugiyama, Hisashi Kashima:
Improving imbalanced classification using near-miss instances. Expert Syst. Appl. 201: 117130 (2022)- [j20]Hiroaki Sasaki, Takashi Takenouchi:
Representation Learning for Maximization of MI, Nonlinear ICA and Nonlinear Subspaces with Robust Density Ratio Estimation. J. Mach. Learn. Res. 23: 231:1-231:55 (2022) - 2021
- [c20]Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi, Hisashi Kashima:
Regret Minimization for Causal Inference on Large Treatment Space. AISTATS 2021: 946-954 - [c19]Shuhei M. Yoshida, Takashi Takenouchi, Masashi Sugiyama:
Lower-Bounded Proper Losses for Weakly Supervised Classification. ICML 2021: 12110-12120 - [c18]Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi, Hisashi Kashima:
Causal Combinatorial Factorization Machines for Set-Wise Recommendation. PAKDD (2) 2021: 498-509 - [i6]Hiroaki Sasaki, Takashi Takenouchi:
A unified view for unsupervised representation learning with density ratio estimation: Maximization of mutual information, nonlinear ICA and nonlinear subspace estimation. CoRR abs/2101.02083 (2021) - [i5]Shuhei M. Yoshida, Takashi Takenouchi, Masashi Sugiyama:
Lower-bounded proper losses for weakly supervised classification. CoRR abs/2103.02893 (2021) - 2020
- [c17]Masatoshi Uehara, Takafumi Kanamori, Takashi Takenouchi, Takeru Matsuda:
A Unified Statistically Efficient Estimation Framework for Unnormalized Models. AISTATS 2020: 809-819 - [c16]Hiroaki Sasaki, Takashi Takenouchi, Ricardo Pio Monti, Aapo Hyvärinen:
Robust contrastive learning and nonlinear ICA in the presence of outliers. UAI 2020: 659-668 - [c15]Masato Ishii, Takashi Takenouchi, Masashi Sugiyama:
Partially Zero-shot Domain Adaptation from Incomplete Target Data with Missing Classes. WACV 2020: 3041-3049 - [i4]Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi, Hisashi Kashima:
Regret Minimization for Causal Inference on Large Treatment Space. CoRR abs/2006.05616 (2020)
2010 – 2019
- 2019
- [c14]Masato Ishii, Takashi Takenouchi, Masashi Sugiyama:
Zero-shot Domain Adaptation Based on Attribute Information. ACML 2019: 473-488 - [c13]Takashi Takenouchi:
Parameter Estimation with Generalized Empirical Localization. GSI 2019: 368-376 - [i3]Masatoshi Uehara, Takafumi Kanamori, Takashi Takenouchi, Takeru Matsuda:
Unified estimation framework for unnormalized models with statistical efficiency. CoRR abs/1901.07710 (2019) - [i2]Masato Ishii, Takashi Takenouchi, Masashi Sugiyama:
Zero-shot Domain Adaptation Based on Attribute Information. CoRR abs/1903.05312 (2019) - [i1]Hiroaki Sasaki, Takashi Takenouchi, Ricardo Pio Monti, Aapo Hyvärinen:
Robust contrastive learning and nonlinear ICA in the presence of outliers. CoRR abs/1911.00265 (2019) - 2018
- [j19]Takashi Takenouchi, Shin Ishii:
Binary classifiers ensemble based on Bregman divergence for multi-class classification. Neurocomputing 273: 424-434 (2018) - 2017
- [j18]Takashi Takenouchi, Takafumi Kanamori:
Statistical Inference with Unnormalized Discrete Models and Localized Homogeneous Divergences. J. Mach. Learn. Res. 18: 56:1-56:26 (2017) - [j17]Takafumi Kanamori, Takashi Takenouchi:
Graph-based composite local Bregman divergences on discrete sample spaces. Neural Networks 95: 44-56 (2017) - 2015
- [j16]Takashi Takenouchi, Osamu Komori, Shinto Eguchi:
Binary Classification with a Pseudo Exponential Model and Its Application for Multi-Task Learning. Entropy 17(8): 5673-5694 (2015) - [j15]Takashi Takenouchi:
A Novel Parameter Estimation Method for Boltzmann Machines. Neural Comput. 27(11): 2423-2446 (2015) - [c12]Kohei Machida, Takashi Takenouchi:
Non-negative Matrix Factorization based on γ-divergence. IJCNN 2015: 1-6 - [c11]Takashi Takenouchi, Takafumi Kanamori:
Empirical Localization of Homogeneous Divergences on Discrete Sample Spaces. NIPS 2015: 820-828 - 2013
- [j14]Takafumi Kanamori, Takashi Takenouchi:
Improving Logitboost with prior knowledge. Inf. Fusion 14(2): 208-219 (2013) - 2012
- [j13]Satoshi Kozawa, Takashi Takenouchi, Kazushi Ikeda:
Subsurface imaging for anti-personal mine detection by Bayesian super-resolution with a smooth-gap prior. Artif. Life Robotics 16(4): 478-481 (2012) - [j12]Takashi Takenouchi, Osamu Komori, Shinto Eguchi:
An Extension of the Receiver Operating Characteristic Curve and AUC-Optimal Classification. Neural Comput. 24(10): 2789-2824 (2012) - [c10]Takashi Takenouchi, Shin Ishii:
A Unified Framework of Binary Classifiers Ensemble for Multi-class Classification. ICONIP (2) 2012: 375-382 - [c9]Kohei Hayashi, Takashi Takenouchi, Ryota Tomioka, Hisashi Kashima:
Self-measuring Similarity for Multi-task Gaussian Process. ICML Unsupervised and Transfer Learning 2012: 145-154 - 2011
- [j11]Kohei Hayashi, Takashi Takenouchi, Tomohiro Shibata, Yuki Kamiya, Daishi Kato, Kazuo Kunieda, Keiji Yamada, Kazushi Ikeda:
Exponential family tensor factorization: an online extension and applications. Knowl. Inf. Syst. 33(1): 57-88 (2011) - [j10]Takashi Takenouchi, Shin Ishii:
Ternary Bradley-Terry model-based decoding for multi-class classification and its extensions. Mach. Learn. 85(3): 249-272 (2011) - 2010
- [c8]Takashi Takenouchi, Kazushi Ikeda:
Theoretical Analysis of Cross-Validation(CV)-EM Algorithm. ICANN (3) 2010: 321-326 - [c7]Kohei Hayashi, Takashi Takenouchi, Tomohiro Shibata, Yuki Kamiya, Daishi Kato, Kazuo Kunieda, Keiji Yamada, Kazushi Ikeda:
Exponential Family Tensor Factorization for Missing-Values Prediction and Anomaly Detection. ICDM 2010: 216-225
2000 – 2009
- 2009
- [j9]Takashi Takenouchi, Shin Ishii:
A Multiclass Classification Method Based on Decoding of Binary Classifiers. Neural Comput. 21(7): 2049-2081 (2009) - 2008
- [j8]Satoshi Osaga, Junichiro Hirayama, Takashi Takenouchi, Shin Ishii:
A probabilistic modeling of MOSAIC learning. Artif. Life Robotics 12(1-2): 167-171 (2008) - [j7]Takashi Takenouchi, Shinto Eguchi, Noboru Murata, Takafumi Kanamori:
Robust Boosting Algorithm Against Mislabeling in Multiclass Problems. Neural Comput. 20(6): 1596-1630 (2008) - 2007
- [j6]Akihiro Tanabe, Kenji Fukumizu, Shigeyuki Oba, Takashi Takenouchi, Shin Ishii:
Parameter estimation for von Mises-Fisher distributions. Comput. Stat. 22(1): 145-157 (2007) - [j5]Takashi Takenouchi, Masaru Ushijima, Shinto Eguchi:
GroupAdaBoost: Accurate Prediction and Selection of Important Genes. Inf. Media Technol. 2(2): 506-513 (2007) - [j4]Takafumi Kanamori, Takashi Takenouchi, Shinto Eguchi, Noboru Murata:
Robust Loss Functions for Boosting. Neural Comput. 19(8): 2183-2244 (2007) - [c6]Satoshi Osaga, Junichiro Hirayama, Takashi Takenouchi, Shin Ishii:
A Probabilistic Model of MOSAIC. FOCI 2007: 41-46 - [c5]Takashi Takenouchi, Shin Ishii:
Multiclass classification as a decoding problem. FOCI 2007: 470-475 - [c4]Junichiro Hirayama, Masashi Nakatomi, Takashi Takenouchi, Shin Ishii:
Bayesian Collaborative Predictors for General User Modeling Tasks. ICONIP (1) 2007: 742-751 - [c3]Takashi Takenouchi, Shin Ishii:
A probabilistic decoding approach to multi-class classification. IJCNN 2007: 2671-2676 - 2006
- [j3]Takafumi Kanamori, Takashi Takenouchi, Noboru Murata:
Geometrical Structure of Boosting Algorithm. New Gener. Comput. 25(1): 117-141 (2006) - 2005
- [c2]Takashi Takenouchi, Masaru Ushijima, Shinto Eguchi:
GroupAdaBoost for Selecting Important Genes. BIBE 2005: 218-221 - 2004
- [j2]Takashi Takenouchi, Shinto Eguchi:
Robustifying AdaBoost by Adding the Naive Error Rate. Neural Comput. 16(4): 767-787 (2004) - [j1]Noboru Murata, Takashi Takenouchi, Takafumi Kanamori, Shinto Eguchi:
Information Geometry of U-Boost and Bregman Divergence. Neural Comput. 16(7): 1437-1481 (2004) - [c1]Takafumi Kanamori, Takashi Takenouchi, Shinto Eguchi, Noboru Murata:
The Most Robust Loss Function for Boosting. ICONIP 2004: 496-501
Coauthor Index
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