Takashi Takenouchi

48 papers A* 2A 4B 3C 2Journal 27Unranked 10

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Bayesian-Like Estimation with Unnormalized Model. GSI (1) Takashi Takenouchi
2022	J	`jnl`	Improving imbalanced classification using near-miss instances. Expert Syst. Appl. Akira Tanimoto, So Yamada, Takashi Takenouchi, Masashi Sugiyama, Hisashi Kashima
2022	J	`jnl`	Representation Learning for Maximization of MI, Nonlinear ICA and Nonlinear Subspaces with Robust Density Ratio Estimation. J. Mach. Learn. Res. Hiroaki Sasaki, Takashi Takenouchi
2021	J	`jnl`	A unified view for unsupervised representation learning with density ratio estimation: Maximization of mutual information, nonlinear ICA and nonlinear subspace estimation. CoRR Hiroaki Sasaki, Takashi Takenouchi
2021	—	`conf`	Causal Combinatorial Factorization Machines for Set-Wise Recommendation. PAKDD (2) Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi, Hisashi Kashima
2021	A*	`conf`	Lower-Bounded Proper Losses for Weakly Supervised Classification. ICML Shuhei M. Yoshida, Takashi Takenouchi, Masashi Sugiyama
2021	J	`jnl`	Lower-bounded proper losses for weakly supervised classification. CoRR Shuhei M. Yoshida, Takashi Takenouchi, Masashi Sugiyama
2021	A	`conf`	Regret Minimization for Causal Inference on Large Treatment Space. AISTATS Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi, Hisashi Kashima
2020	A	`conf`	A Unified Statistically Efficient Estimation Framework for Unnormalized Models. AISTATS Masatoshi Uehara, Takafumi Kanamori, Takashi Takenouchi, Takeru Matsuda
2020	A	`conf`	Partially Zero-shot Domain Adaptation from Incomplete Target Data with Missing Classes. WACV Masato Ishii, Takashi Takenouchi, Masashi Sugiyama
2020	J	`jnl`	Regret Minimization for Causal Inference on Large Treatment Space. CoRR Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi, Hisashi Kashima
2020	A	`conf`	Robust contrastive learning and nonlinear ICA in the presence of outliers. UAI Hiroaki Sasaki, Takashi Takenouchi, Ricardo Pio Monti, Aapo Hyvärinen
2019	—	`conf`	Parameter Estimation with Generalized Empirical Localization. GSI Takashi Takenouchi
2019	J	`jnl`	Robust contrastive learning and nonlinear ICA in the presence of outliers. CoRR Hiroaki Sasaki, Takashi Takenouchi, Ricardo Pio Monti, Aapo Hyvärinen
2019	J	`jnl`	Unified estimation framework for unnormalized models with statistical efficiency. CoRR Masatoshi Uehara, Takafumi Kanamori, Takashi Takenouchi, Takeru Matsuda
2019	C	`conf`	Zero-shot Domain Adaptation Based on Attribute Information. ACML Masato Ishii, Takashi Takenouchi, Masashi Sugiyama
2019	J	`jnl`	Zero-shot Domain Adaptation Based on Attribute Information. CoRR Masato Ishii, Takashi Takenouchi, Masashi Sugiyama
2018	J	`jnl`	Binary classifiers ensemble based on Bregman divergence for multi-class classification. Neurocomputing Takashi Takenouchi, Shin Ishii
2017	J	`jnl`	Graph-based composite local Bregman divergences on discrete sample spaces. Neural Networks Takafumi Kanamori, Takashi Takenouchi
2017	J	`jnl`	Statistical Inference with Unnormalized Discrete Models and Localized Homogeneous Divergences. J. Mach. Learn. Res. Takashi Takenouchi, Takafumi Kanamori
2015	J	`jnl`	A Novel Parameter Estimation Method for Boltzmann Machines. Neural Comput. Takashi Takenouchi
2015	J	`jnl`	Binary Classification with a Pseudo Exponential Model and Its Application for Multi-Task Learning. Entropy Takashi Takenouchi, Osamu Komori, Shinto Eguchi
2015	—	`conf`	Empirical Localization of Homogeneous Divergences on Discrete Sample Spaces. NIPS Takashi Takenouchi, Takafumi Kanamori
2015	B	`conf`	Non-negative Matrix Factorization based on γ-divergence. IJCNN Kohei Machida, Takashi Takenouchi
2013	J	`jnl`	Improving Logitboost with prior knowledge. Inf. Fusion Takafumi Kanamori, Takashi Takenouchi
2012	—	`conf`	A Unified Framework of Binary Classifiers Ensemble for Multi-class Classification. ICONIP (2) Takashi Takenouchi, Shin Ishii
2012	J	`jnl`	An Extension of the Receiver Operating Characteristic Curve and AUC-Optimal Classification. Neural Comput. Takashi Takenouchi, Osamu Komori, Shinto Eguchi
2012	—	`conf`	Self-measuring Similarity for Multi-task Gaussian Process. ICML Unsupervised and Transfer Learning Kohei Hayashi, Takashi Takenouchi, Ryota Tomioka, Hisashi Kashima
2012	J	`jnl`	Subsurface imaging for anti-personal mine detection by Bayesian super-resolution with a smooth-gap prior. Artif. Life Robotics Satoshi Kozawa, Takashi Takenouchi, Kazushi Ikeda
2011	J	`jnl`	Exponential family tensor factorization: an online extension and applications. Knowl. Inf. Syst. Kohei Hayashi, Takashi Takenouchi, Tomohiro Shibata, Yuki Kamiya, Daishi Kato, Kazuo Kunieda, Keiji Yamada, Kazushi Ikeda
2011	J	`jnl`	Ternary Bradley-Terry model-based decoding for multi-class classification and its extensions. Mach. Learn. Takashi Takenouchi, Shin Ishii
2010	A*	`conf`	Exponential Family Tensor Factorization for Missing-Values Prediction and Anomaly Detection. ICDM Kohei Hayashi, Takashi Takenouchi, Tomohiro Shibata, Yuki Kamiya, Daishi Kato, Kazuo Kunieda, Keiji Yamada, Kazushi Ikeda
2010	—	`conf`	Theoretical Analysis of Cross-Validation(CV)-EM Algorithm. ICANN (3) Takashi Takenouchi, Kazushi Ikeda
2009	J	`jnl`	A Multiclass Classification Method Based on Decoding of Binary Classifiers. Neural Comput. Takashi Takenouchi, Shin Ishii
2008	J	`jnl`	A probabilistic modeling of MOSAIC learning. Artif. Life Robotics Satoshi Osaga, Junichiro Hirayama, Takashi Takenouchi, Shin Ishii
2008	J	`jnl`	Robust Boosting Algorithm Against Mislabeling in Multiclass Problems. Neural Comput. Takashi Takenouchi, Shinto Eguchi, Noboru Murata, Takafumi Kanamori
2007	—	`conf`	A Probabilistic Model of MOSAIC. FOCI Satoshi Osaga, Junichiro Hirayama, Takashi Takenouchi, Shin Ishii
2007	B	`conf`	A probabilistic decoding approach to multi-class classification. IJCNN Takashi Takenouchi, Shin Ishii
2007	—	`conf`	Bayesian Collaborative Predictors for General User Modeling Tasks. ICONIP (1) Junichiro Hirayama, Masashi Nakatomi, Takashi Takenouchi, Shin Ishii
2007	J	`jnl`	GroupAdaBoost: Accurate Prediction and Selection of Important Genes. Inf. Media Technol. Takashi Takenouchi, Masaru Ushijima, Shinto Eguchi
2007	—	`conf`	Multiclass classification as a decoding problem. FOCI Takashi Takenouchi, Shin Ishii
2007	J	`jnl`	Parameter estimation for von Mises-Fisher distributions. Comput. Stat. Akihiro Tanabe, Kenji Fukumizu, Shigeyuki Oba, Takashi Takenouchi, Shin Ishii
2007	J	`jnl`	Robust Loss Functions for Boosting. Neural Comput. Takafumi Kanamori, Takashi Takenouchi, Shinto Eguchi, Noboru Murata
2006	J	`jnl`	Geometrical Structure of Boosting Algorithm. New Gener. Comput. Takafumi Kanamori, Takashi Takenouchi, Noboru Murata
2005	C	`conf`	GroupAdaBoost for Selecting Important Genes. BIBE Takashi Takenouchi, Masaru Ushijima, Shinto Eguchi
2004	J	`jnl`	Information Geometry of U-Boost and Bregman Divergence. Neural Comput. Noboru Murata, Takashi Takenouchi, Takafumi Kanamori, Shinto Eguchi
2004	J	`jnl`	Robustifying AdaBoost by Adding the Naive Error Rate. Neural Comput. Takashi Takenouchi, Shinto Eguchi
2004	B	`conf`	The Most Robust Loss Function for Boosting. ICONIP Takafumi Kanamori, Takashi Takenouchi, Shinto Eguchi, Noboru Murata