Takashi Takenouchi

发表

A Unified Statistically Efficient Estimation Framework for Unnormalized Models

Masatoshi Uehara, Takafumi Kanamori, Takeru Matsuda, 2020, AISTATS.

Empirical Localization of Homogeneous Divergences on Discrete Sample Spaces

Takafumi Kanamori, Takashi Takenouchi, 2015, NIPS.

Combining multiple decisions: applications to bioinformatics

Shin Ishii, Takashi Takenouchi, Naoto Yukinawa, 2008 .

A Multiclass Classification Method Based on Decoding of Binary Classifiers

Shin Ishii, Takashi Takenouchi, S. Ishii, 2009, Neural Computation.

Multiclass classification as a decoding problem

Shin Ishii, Takashi Takenouchi, 2007, 2007 IEEE Symposium on Foundations of Computational Intelligence.

Exponential Family Tensor Factorization for Missing-Values Prediction and Anomaly Detection

Kazushi Ikeda, Daishi Kato, Kazuo Kunieda, 2010, 2010 IEEE International Conference on Data Mining.

Robust Model Selection for Classification of Microarrays

Shin Ishii, Ikumi Suzuki, Takashi Takenouchi, 2009, Cancer informatics.

A probabilistic decoding approach to multi-class classification

Shin Ishii, Takashi Takenouchi, 2007, 2007 International Joint Conference on Neural Networks.

Parameter Estimation with Generalized Empirical Localization

Takashi Takenouchi, 2019, GSI.

Bayesian Collaborative Predictors for General User Modeling Tasks

Shin Ishii, Junichiro Hirayama, Takashi Takenouchi, 2007, ICONIP.

An Extension of the Receiver Operating Characteristic Curve and AUC-Optimal Classification

Shinto Eguchi, Takashi Takenouchi, Osamu Komori, 2012, Neural Computation.

Zero-shot Domain Adaptation Based on Attribute Information pdf

Masashi Sugiyama, Masato Ishii, Takashi Takenouchi, 2019, ACML.

Bayesian decoder for multi-class classification by mixture of divergence

Shin Ishii, Takashi Takenouchi, Noboru Murata, 2010 .

Theoretical Analysis of Cross-Validation(CV)-EM Algorithm

Kazushi Ikeda, Takashi Takenouchi, 2010, ICANN.

Ternary Bradley-Terry model-based decoding for multi-class classification and its extensions

Shin Ishii, Takashi Takenouchi, S. Ishii, 2011, 2008 IEEE Workshop on Machine Learning for Signal Processing.

Exponential family tensor factorization: an online extension and applications

Kazushi Ikeda, Daishi Kato, Kazuo Kunieda, 2012, Knowledge and Information Systems.

Improving Logitboost with prior knowledge

Takafumi Kanamori, Takashi Takenouchi, 2013, Inf. Fusion.

Partially Zero-shot Domain Adaptation from Incomplete Target Data with Missing Classes

Masashi Sugiyama, Takashi Takenouchi, Masato Ishii, 2020, 2020 IEEE Winter Conference on Applications of Computer Vision (WACV).

Robust Loss Functions for Boosting

Takafumi Kanamori, Noboru Murata, Shinto Eguchi, 2007, Neural Computation.

Statistical Inference with Unnormalized Discrete Models and Localized Homogeneous Divergences

Takafumi Kanamori, Takashi Takenouchi, T. Kanamori, 2017, J. Mach. Learn. Res..

Ternary Bradley-Terry model-based decoding for multi-class classification

Shin Ishii, Takashi Takenouchi, S. Ishii, 2008 .

GroupAdaBoost: Accurate Prediction and Selection of Important Genes

Shinto Eguchi, Takashi Takenouchi, Masaru Ushijima, 2007 .

A Novel Parameter Estimation Method for Boltzmann Machines

Takashi Takenouchi, 2015, Neural Computation.

Robust Boosting Algorithm Against Mislabeling in Multiclass Problems

Takafumi Kanamori, Noboru Murata, Shinto Eguchi, 2008, Neural Computation.

Self-measuring Similarity for Multi-task Gaussian Process

Hisashi Kashima, Ryota Tomioka, Kohei Hayashi, 2011, ICML Unsupervised and Transfer Learning.

Information Geometry of U-Boost and Bregman Divergence

Takafumi Kanamori, Noboru Murata, Shinto Eguchi, 2004, Neural Computation.

A probabilistic modeling of MOSAIC learning

Shin Ishii, Jun-ichiro Hirayama, Takashi Takenouchi, 2007, Artificial Life and Robotics.

Part 6: Geometrical Structure of Boosting Algorithm

Takafumi Kanamori, Noboru Murata, Takashi Takenouchi, 2006, New Generation Computing.

Regret Minimization for Causal Inference on Large Treatment Space pdf

Tomoya Sakai, Hisashi Kashima, Takashi Takenouchi, 2020, ArXiv.

Analysis of Advance Cues in Predicting Volleyball Attacks

Takashi Takenouchi, Akira Nishino, Enji Okuda, 1991 .

A Probabilistic Model of MOSAIC

Shin Ishii, Junichiro Hirayama, Takashi Takenouchi, 2007, 2007 IEEE Symposium on Foundations of Computational Intelligence.

Binary classifiers ensemble based on Bregman divergence for multi-class classification

Shin Ishii, Takashi Takenouchi, 2018, Neurocomputing.

A unified view for unsupervised representation learning with density ratio estimation: Maximization of mutual information, nonlinear ICA and nonlinear subspace estimation pdf

Hiroaki Sasaki, Takashi Takenouchi, H. Sasaki, 2021, ArXiv.

A novel boosting algorithm for multi-task learning based on the Itakuda-Saito divergence

Shinto Eguchi, Takashi Takenouchi, Osamu Komori, 2015 .

COLLABORATIVE PREDICTION BY MULTIPLE BAYESIAN NETWORKS AND ITS APPLICATION TO PRINTER USAGE MODELING

Shin Ishii, Takashi Takenouchi, Masashi Nakatomi, 2008 .

Subsurface imaging for anti-personal mine detection by Bayesian super-resolution with a smooth-gap prior

Kazushi Ikeda, Takashi Takenouchi, Satoshi Kozawa, 2011, Artificial Life and Robotics.

The Most Robust Loss Function for Boosting

Takafumi Kanamori, Noboru Murata, Shinto Eguchi, 2004, ICONIP.

GroupAdaBoost for selecting important genes

Shinto Eguchi, Takashi Takenouchi, Masaru Ushijima, 2005, Fifth IEEE Symposium on Bioinformatics and Bioengineering (BIBE'05).

Binary Classification with a Pseudo Exponential Model and Its Application for Multi-Task Learning

Shinto Eguchi, Takashi Takenouchi, Osamu Komori, 2015, Entropy.

Robustifying AdaBoost by Adding the Naive Error Rate

Shinto Eguchi, Takashi Takenouchi, 2004, Neural Computation.

Parameter estimation for von Mises–Fisher distributions

Shin Ishii, Kenji Fukumizu, Takashi Takenouchi, 2007, Comput. Stat..

Unified efficient estimation framework for unnormalized models

Masatoshi Uehara, Takafumi Kanamori, Takeru Matsuda, 2019 .

Statistical modeling of robust non-negative matrix factorization based on \(\gamma \)-divergence and its applications

Takashi Takenouchi, Kohei Machida, 2019 .

A Unified Framework of Binary Classifiers Ensemble for Multi-class Classification

Shin Ishii, Takashi Takenouchi, 2012, ICONIP.

Unified estimation framework for unnormalized models with statistical efficiency pdf

Masatoshi Uehara, Takafumi Kanamori, Takeru Matsuda, 2019, ArXiv.

Robust contrastive learning and nonlinear ICA in the presence of outliers pdf

Aapo Hyvärinen, Ricardo Pio Monti, Hiroaki Sasaki, 2019, UAI.

Subsurface imaging by Bayesian superresolution for antipersonal mine detection using ground penetrating radar (Special section on papers awarded the Student Paper Award at NCSP'10)

Kazushi Ikeda, Takashi Takenouchi, Satoshi Kozawa, 2010 .

Non-negative Matrix Factorization based on γ-divergence

Takashi Takenouchi, Kohei Machida, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

Graph-based composite local Bregman divergences on discrete sample spaces

Takafumi Kanamori, Takashi Takenouchi, T. Kanamori, 2016, Neural Networks.

Causal Combinatorial Factorization Machines for Set-Wise Recommendation

Hisashi Kashima, Takashi Takenouchi, Akira Tanimoto, 2021, PAKDD.

Lower-bounded proper losses for weakly supervised classification pdf

Masashi Sugiyama, Takashi Takenouchi, Shuhei M. Yoshida, 2021, ICML.