Takashi Takenouchi

CoRR, 2021

Causal Combinatorial Factorization Machines for Set-Wise Recommendation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2021

Lower-Bounded Proper Losses for Weakly Supervised Classification.

[BibT_eX]

[DOI]

Shuhei M. Yoshida

Masashi Sugiyama

Proceedings of the 38th International Conference on Machine Learning, 2021

Regret Minimization for Causal Inference on Large Treatment Space.

[BibT_eX]

[DOI]

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

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

[BibT_eX]

[DOI]

Masato Ishii

Masashi Sugiyama

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

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

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

A Unified Statistically Efficient Estimation Framework for Unnormalized Models.

[BibT_eX]

[DOI]

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Unified estimation framework for unnormalized models with statistical efficiency.

[BibT_eX]

[DOI]

CoRR, 2019

Parameter Estimation with Generalized Empirical Localization.

[BibT_eX]

[DOI]

Proceedings of the Geometric Science of Information - 4th International Conference, 2019

Zero-shot Domain Adaptation Based on Attribute Information.

[BibT_eX]

[DOI]

Masato Ishii

Masashi Sugiyama

Proceedings of The 11th Asian Conference on Machine Learning, 2019

2018

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

[BibT_eX]

[DOI]

Neurocomputing, 2018

2017

Graph-based composite local Bregman divergences on discrete sample spaces.

[BibT_eX]

[DOI]

Neural Networks, 2017

Statistical Inference with Unnormalized Discrete Models and Localized Homogeneous Divergences.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2017

2015

A Novel Parameter Estimation Method for Boltzmann Machines.

[BibT_eX]

[DOI]

Neural Comput., 2015

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

[BibT_eX]

[DOI]

Osamu Komori

Entropy, 2015

Empirical Localization of Homogeneous Divergences on Discrete Sample Spaces.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Non-negative Matrix Factorization based on γ-divergence.

[BibT_eX]

[DOI]

Kohei Machida

Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

2013

Improving Logitboost with prior knowledge.

[BibT_eX]

[DOI]

Inf. Fusion, 2013

2012

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

[BibT_eX]

[DOI]

Osamu Komori

Neural Comput., 2012

Self-measuring Similarity for Multi-task Gaussian Process.

[BibT_eX]

[DOI]

Proceedings of the Unsupervised and Transfer Learning, 2012

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

[BibT_eX]

[DOI]

Satoshi Kozawa

Kazushi Ikeda

Artif. Life Robotics, 2012

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

[BibT_eX]

[DOI]

Proceedings of the Neural Information Processing - 19th International Conference, 2012

2011

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

[BibT_eX]

[DOI]

Mach. Learn., 2011

Exponential family tensor factorization: an online extension and applications.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., 2011

2010

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

[BibT_eX]

[DOI]

Proceedings of the ICDM 2010, 2010

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

[BibT_eX]

[DOI]

Kazushi Ikeda

Proceedings of the Artificial Neural Networks - ICANN 2010, 2010

2009

A Multiclass Classification Method Based on Decoding of Binary Classifiers.

[BibT_eX]

[DOI]

Neural Comput., 2009

2008

Robust Boosting Algorithm Against Mislabeling in Multiclass Problems.

[BibT_eX]

[DOI]

Neural Comput., 2008

A probabilistic modeling of MOSAIC learning.

[BibT_eX]

[DOI]

Artif. Life Robotics, 2008

2007

Robust Loss Functions for Boosting.

[BibT_eX]

[DOI]

Neural Comput., 2007

GroupAdaBoost: Accurate Prediction and Selection of Important Genes.

[BibT_eX]

[DOI]

Masaru Ushijima

Inf. Media Technol., 2007

Parameter estimation for von Mises-Fisher distributions.

[BibT_eX]

[DOI]

Comput. Stat., 2007

A probabilistic decoding approach to multi-class classification.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2007

Bayesian Collaborative Predictors for General User Modeling Tasks.

[BibT_eX]

[DOI]

Proceedings of the Neural Information Processing, 14th International Conference, 2007

Multiclass classification as a decoding problem.

[BibT_eX]

[DOI]

Proceedings of the IEEE Symposium on Foundations of Computational Intelligence, 2007

A Probabilistic Model of MOSAIC.

[BibT_eX]

[DOI]

Proceedings of the IEEE Symposium on Foundations of Computational Intelligence, 2007

2006

Geometrical Structure of Boosting Algorithm.

[BibT_eX]

[DOI]

Noboru Murata

New Gener. Comput., 2006

2005

GroupAdaBoost for Selecting Important Genes.

[BibT_eX]

[DOI]

Masaru Ushijima

Proceedings of the Fifth IEEE International Symposium on Bioinformatic and Bioengineering (BIBE 2005), 2005

2004

Robustifying AdaBoost by Adding the Naive Error Rate.

[BibT_eX]

[DOI]