Takashi Takenouchi

Publication Activity (10 Years)

Years Active: 2004-2022
Publications (10 Years): 23

Top Topics

Statistical Inference

Spatial Constraints

Parameter Estimation

Unsupervised Classification

Top Venues

J. Mach. Learn. Res.

Publications

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 (2022)
Akira Tanimoto, So Yamada, Takashi Takenouchi, Masashi Sugiyama, Hisashi Kashima
Improving imbalanced classification using near-miss instances. Expert Syst. Appl. 201 (2022)
Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi, Hisashi Kashima
Regret Minimization for Causal Inference on Large Treatment Space. AISTATS (2021)
Shuhei M. Yoshida, Takashi Takenouchi, Masashi Sugiyama
Lower-bounded proper losses for weakly supervised classification. CoRR (2021)
Shuhei M. Yoshida, Takashi Takenouchi, Masashi Sugiyama
Lower-Bounded Proper Losses for Weakly Supervised Classification. ICML (2021)
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 (2021)
Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi, Hisashi Kashima
Causal Combinatorial Factorization Machines for Set-Wise Recommendation. PAKDD (2) (2021)
Hiroaki Sasaki, Takashi Takenouchi, Ricardo Pio Monti, Aapo Hyvärinen
Robust contrastive learning and nonlinear ICA in the presence of outliers. UAI (2020)
Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi, Hisashi Kashima
Regret Minimization for Causal Inference on Large Treatment Space. CoRR (2020)
Masatoshi Uehara, Takafumi Kanamori, Takashi Takenouchi, Takeru Matsuda
A Unified Statistically Efficient Estimation Framework for Unnormalized Models. AISTATS (2020)
Masato Ishii, Takashi Takenouchi, Masashi Sugiyama
Partially Zero-shot Domain Adaptation from Incomplete Target Data with Missing Classes. WACV (2020)
Takashi Takenouchi
Parameter Estimation with Generalized Empirical Localization. GSI (2019)
Hiroaki Sasaki, Takashi Takenouchi, Ricardo Pio Monti, Aapo Hyvärinen
Robust contrastive learning and nonlinear ICA in the presence of outliers. CoRR (2019)
Masato Ishii, Takashi Takenouchi, Masashi Sugiyama
Zero-shot Domain Adaptation Based on Attribute Information. CoRR (2019)
Masato Ishii, Takashi Takenouchi, Masashi Sugiyama
Zero-shot Domain Adaptation Based on Attribute Information. ACML (2019)
Masatoshi Uehara, Takafumi Kanamori, Takashi Takenouchi, Takeru Matsuda
Unified estimation framework for unnormalized models with statistical efficiency. CoRR (2019)
Takashi Takenouchi, Shin Ishii
Binary classifiers ensemble based on Bregman divergence for multi-class classification. Neurocomputing 273 (2018)
Takashi Takenouchi, Takafumi Kanamori
Statistical Inference with Unnormalized Discrete Models and Localized Homogeneous Divergences. J. Mach. Learn. Res. 18 (2017)
Takafumi Kanamori, Takashi Takenouchi
Graph-based composite local Bregman divergences on discrete sample spaces. Neural Networks 95 (2017)
Kohei Machida, Takashi Takenouchi
Non-negative Matrix Factorization based on γ-divergence. IJCNN (2015)
Takashi Takenouchi, Osamu Komori, Shinto Eguchi
Binary Classification with a Pseudo Exponential Model and Its Application for Multi-Task Learning. Entropy 17 (8) (2015)
Takashi Takenouchi
A Novel Parameter Estimation Method for Boltzmann Machines. Neural Comput. 27 (11) (2015)
Takashi Takenouchi, Takafumi Kanamori
Empirical Localization of Homogeneous Divergences on Discrete Sample Spaces. NIPS (2015)
Takafumi Kanamori, Takashi Takenouchi
Improving Logitboost with prior knowledge. Inf. Fusion 14 (2) (2013)
Takashi Takenouchi, Osamu Komori, Shinto Eguchi
An Extension of the Receiver Operating Characteristic Curve and AUC-Optimal Classification. Neural Comput. 24 (10) (2012)
Takashi Takenouchi, Shin Ishii
A Unified Framework of Binary Classifiers Ensemble for Multi-class Classification. ICONIP (2) (2012)
Kohei Hayashi, Takashi Takenouchi, Ryota Tomioka, Hisashi Kashima
Self-measuring Similarity for Multi-task Gaussian Process. ICML Unsupervised and Transfer Learning (2012)
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) (2012)
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) (2011)
Takashi Takenouchi, Shin Ishii
Ternary Bradley-Terry model-based decoding for multi-class classification and its extensions. Mach. Learn. 85 (3) (2011)
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)
Takashi Takenouchi, Kazushi Ikeda
Theoretical Analysis of Cross-Validation(CV)-EM Algorithm. ICANN (3) (2010)
Takashi Takenouchi, Shin Ishii
A Multiclass Classification Method Based on Decoding of Binary Classifiers. Neural Comput. 21 (7) (2009)
Takashi Takenouchi, Shinto Eguchi, Noboru Murata, Takafumi Kanamori
Robust Boosting Algorithm Against Mislabeling in Multiclass Problems. Neural Comput. 20 (6) (2008)
Satoshi Osaga, Junichiro Hirayama, Takashi Takenouchi, Shin Ishii
A probabilistic modeling of MOSAIC learning. Artif. Life Robotics 12 (1-2) (2008)
Junichiro Hirayama, Masashi Nakatomi, Takashi Takenouchi, Shin Ishii
Bayesian Collaborative Predictors for General User Modeling Tasks. ICONIP (1) (2007)
Satoshi Osaga, Junichiro Hirayama, Takashi Takenouchi, Shin Ishii
A Probabilistic Model of MOSAIC. FOCI (2007)
Takashi Takenouchi, Shin Ishii
A probabilistic decoding approach to multi-class classification. IJCNN (2007)
Takafumi Kanamori, Takashi Takenouchi, Shinto Eguchi, Noboru Murata
Robust Loss Functions for Boosting. Neural Comput. 19 (8) (2007)
Takashi Takenouchi, Masaru Ushijima, Shinto Eguchi
GroupAdaBoost: Accurate Prediction and Selection of Important Genes. Inf. Media Technol. 2 (2) (2007)
Takashi Takenouchi, Shin Ishii
Multiclass classification as a decoding problem. FOCI (2007)
Akihiro Tanabe, Kenji Fukumizu, Shigeyuki Oba, Takashi Takenouchi, Shin Ishii
Parameter estimation for von Mises-Fisher distributions. Comput. Stat. 22 (1) (2007)
Takafumi Kanamori, Takashi Takenouchi, Noboru Murata
Geometrical Structure of Boosting Algorithm. New Gener. Comput. 25 (1) (2006)
Takashi Takenouchi, Masaru Ushijima, Shinto Eguchi
GroupAdaBoost for Selecting Important Genes. BIBE (2005)
Takafumi Kanamori, Takashi Takenouchi, Shinto Eguchi, Noboru Murata
The Most Robust Loss Function for Boosting. ICONIP (2004)
Noboru Murata, Takashi Takenouchi, Takafumi Kanamori, Shinto Eguchi
Information Geometry of U-Boost and Bregman Divergence. Neural Comput. 16 (7) (2004)
Takashi Takenouchi, Shinto Eguchi
Robustifying AdaBoost by Adding the Naive Error Rate. Neural Comput. 16 (4) (2004)