T. Kanamori

发表

Statistical Asymptotic Theory of Active Learning

T. Kanamori, 2002 .

Active learning algorithm using the maximum weighted log-likelihood estimator

Hidetoshi Shimodaira, T. Kanamori, 2003 .

Density Ratio Estimation: A Comprehensive Review

Masashi Sugiyama, T. Kanamori, Teruyuki Suzuki, 2010 .

Density-ratio matching under the Bregman divergence: a unified framework of density-ratio estimation

Masashi Sugiyama, T. Kanamori, Teruyuki Suzuki, 2012 .

A Least-squares Approach to Direct Importance Estimation

Takafumi Kanamori, Masashi Sugiyama, Shohei Hido, 2009, J. Mach. Learn. Res..

$f$ -Divergence Estimation and Two-Sample Homogeneity Test Under Semiparametric Density-Ratio Models

Takafumi Kanamori, Masashi Sugiyama, Taiji Suzuki, 2010, IEEE Transactions on Information Theory.

Condition Number Analysis of Kernel-based Density Ratio Estimation

Masashi Sugiyama, Taiji Suzuki, T. Kanamori, 2009, 0912.2800.

Density Ratio Estimation in Machine Learning

Takafumi Kanamori, Masashi Sugiyama, Taiji Suzuki, 2012 .

Efficient Direct Density Ratio Estimation for Non-stationarity Adaptation and Outlier Detection

Takafumi Kanamori, Masashi Sugiyama, Shohei Hido, 2008, NIPS.

Least-squares two-sample test

Takafumi Kanamori, Masashi Sugiyama, Taiji Suzuki, 2011, Neural Networks.

Robust estimation under heavy contamination using unnormalized models

T. Kanamori, H. Fujisawa, 2014 .

A Least-squares Approach to Mutual Information Estimation with Application in Variable Selection

Masashi Sugiyama, Taiji Suzuki, T. Kanamori, 2008 .

Least-squares Conditional Density Estimation Masashi Sugiyama

Masashi Sugiyama, Taiji Suzuki, I. Takeuchi, 2009 .

Robust Estimation under Heavy Contamination using Enlarged Models

T. Kanamori, H. Fujisawa, 2013, 1311.5301.

Robust Estimation of Conditional Mean by the Linear Combination of Quantile Regressions

T. Kanamori, 2008 .

Affine invariant divergences associated with proper composite scoring rules and their applications

Takafumi Kanamori, Hironori Fujisawa, T. Kanamori, 2014 .

A Bregman Extension of quasi-Newton updates II: Convergence and Robustness Properties

Takafumi Kanamori, Atsumi Ohara, A. Ohara, 2010, 1010.2846.

Estimating Density Models with Truncation Boundaries using Score Matching

T. Kanamori, Song Liu, Daniel J. Williams, 2019, J. Mach. Learn. Res..

Estimating Density Models with Truncation Boundaries

T. Kanamori, Song Liu, Daniel J. Williams, 2019 .

Applications of Density Ratios in Machine Learning

Takafumi Kanamori, Masashi Sugiyama, Taiji Suzuki, 2012 .

Density Ratio Estimation : A Comprehensive Review (Statistical Experiment and Its Related Topics)

Takafumi Kanamori, Masashi Sugiyama, Taiji Suzuki, 2010 .

Density Ratio Estimation in Machine Learning: Preface

Takafumi Kanamori, Masashi Sugiyama, Taiji Suzuki, 2012 .

Mode estimation on matrix manifolds: Convergence and robustness

T. Kanamori, H. Sasaki, J. Hirayama, 2022, AISTATS.

Loss functions for multiclass boosting (情報論的学習理論と機械学習)

Takafumi Kanamori, T. Kanamori, 2010 .

Boosting

T. Kanamori, Kohei Hatano, Osamu Watanabe, 2008, American Potato Journal.

Deep Self-Supervised Learning of Speech Denoising from Noisy Speeches

T. Kanamori, K. Takanashi, Yutaro Sanada, 2022, INTERSPEECH.

Semi-supervised learning with density-ratio estimation

T. Kanamori, Masanori Kawakita, 2012, Machine Learning.

Numerical study of learning algorithms on Stiefel manifold

T. Kanamori, A. Takeda, 2013, Computational Management Science.

Parallel distributed block coordinate descent methods based on pairwise comparison oracle

T. Kanamori, Kota Matsui, Wataru Kumagai, 2016, Journal of Global Optimization.

Worst-Case Violation of Sampled Convex Programs for Optimization with Uncertainty

T. Kanamori, A. Takeda, 2011, Journal of Optimization Theory and Applications.

Density Ratio Estimation in Machine Learning: Conclusions and Future Directions

Takafumi Kanamori, Masashi Sugiyama, Taiji Suzuki, 2012 .

Mutual Information Estimation

Takafumi Kanamori, Masashi Sugiyama, Taiji Suzuki, 2012 .

A Unified Statistically Efficient Estimation Framework for Unnormalized Models

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

Unified efficient estimation framework for unnormalized models

Masatoshi Uehara, Takafumi Kanamori, Takeru Matsuda, 2019 .

Unified estimation framework for unnormalized models with statistical efficiency pdf

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

Theoretical Analysis of Density Ratio Estimation

Takafumi Kanamori, Masashi Sugiyama, Taiji Suzuki, 2010, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

Pool-based active learning with optimal sampling distribution and its information geometrical interpretation

Takafumi Kanamori, T. Kanamori, 2007, Neurocomputing.

Approximating Mutual Information by Maximum Likelihood Density Ratio Estimation

Takafumi Kanamori, Masashi Sugiyama, Taiji Suzuki, 2008, FSDM.

Extended Robust Support Vector Machine Based on Financial Risk Minimization

Takafumi Kanamori, Akiko Takeda, Shuhei Fujiwara, 2014, Neural Computation.

A Conjugate Property between Loss Functions and Uncertainty Sets in Classification Problems pdf

Takafumi Kanamori, Akiko Takeda, Taiji Suzuki, 2012, COLT.

Numerical study of reciprocal recommendation with domain matching

Takafumi Kanamori, Naoya Osugi, Kotaro Sudo, 2019, Japanese Journal of Statistics and Data Science.

Numerical study of learning algorithms on Stiefel manifold

Takafumi Kanamori, Akiko Takeda, T. Kanamori, 2014, Comput. Manag. Sci..

Using financial risk measures for analyzing generalization performance of machine learning models

Takafumi Kanamori, Akiko Takeda, T. Kanamori, 2014, Neural Networks.

Computational complexity of kernel-based density-ratio estimation: a condition number analysis

Takafumi Kanamori, Masashi Sugiyama, Taiji Suzuki, 2012, Machine Learning.

Mutual information estimation reveals global associations between stimuli and biological processes

Takafumi Kanamori, Masashi Sugiyama, Taiji Suzuki, 2009, BMC Bioinformatics.

Least-Squares Conditional Density Estimation

Takafumi Kanamori, Masashi Sugiyama, Taiji Suzuki, 2010, IEICE Trans. Inf. Syst..

Robust Label Prediction via Label Propagation and Geodesic k-Nearest Neighbor in Online Semi-Supervised Learning

Takafumi Kanamori, Yuichiro Wada, Wataru Kumagai, 2019, IEICE Trans. Inf. Syst..

Breakdown Point of Robust Support Vector Machines

Takafumi Kanamori, Akiko Takeda, Shuhei Fujiwara, 2017, Entropy.

Robust Boosting Algorithm Against Mislabeling in Multiclass Problems

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

Parallel distributed block coordinate descent methods based on pairwise comparison oracle

Takafumi Kanamori, Kota Matsui, Wataru Kumagai, 2014, J. Glob. Optim..

Towards Understanding the Mechanism of Contrastive Learning via Similarity Structure: A Theoretical Analysis

T. Kanamori, Takumi Nakagawa, Yuichiro Wada, 2023, ECML/PKDD.

Relative Density-Ratio Estimation for Robust Distribution Comparison

Takafumi Kanamori, Masashi Sugiyama, Taiji Suzuki, 2011, Neural Computation.

Statistical Inference with Unnormalized Discrete Models and Localized Homogeneous Divergences

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

A Bregman extension of quasi-Newton updates I: an information geometrical framework

Takafumi Kanamori, Atsumi Ohara, A. Ohara, 2010, Optim. Methods Softw..

Information Geometry of U-Boost and Bregman Divergence

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

Statistical analysis of kernel-based least-squares density-ratio estimation

Takafumi Kanamori, Masashi Sugiyama, Taiji Suzuki, 2012, Machine Learning.

Estimating Density Models with Complex Truncation Boundaries pdf

Takafumi Kanamori, Song Liu, T. Kanamori, 2019, ArXiv.

Robust Loss Functions for Boosting

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

Efficiency Bound of Local Z-Estimators on Discrete Sample Spaces

Takafumi Kanamori, T. Kanamori, 2016, Entropy.

Uncertainty propagation for dropout-based Bayesian neural networks

Takafumi Kanamori, Wataru Kumagai, Yuki Mae, 2021, Neural Networks.

Robustness of learning algorithms using hinge loss with outlier indicators

Takafumi Kanamori, Akiko Takeda, Shuhei Fujiwara, 2017, Neural Networks.

DC Algorithm for Extended Robust Support Vector Machine

Takafumi Kanamori, Akiko Takeda, Shuhei Fujiwara, 2017, Neural Computation.

Graph-based composite local Bregman divergences on discrete sample spaces

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

A Bregman extension of quasi-Newton updates II: Analysis of robustness properties

Takafumi Kanamori, Atsumi Ohara, A. Ohara, 2013, J. Comput. Appl. Math..

Risk bound of transfer learning using parametric feature mapping and its application to sparse coding

Takafumi Kanamori, Wataru Kumagai, T. Kanamori, 2019, Machine Learning.

Statistical outlier detection using direct density ratio estimation

Takafumi Kanamori, Masashi Sugiyama, Hisashi Kashima, 2011, Knowledge and Information Systems.

Density-Difference Estimation

Takafumi Kanamori, Masashi Sugiyama, Taiji Suzuki, 2012, Neural Computation.

Variable Selection for Nonparametric Learning with Power Series Kernels

Takafumi Kanamori, Kenta Kanamori, Kota Matsui, 2018, Neural Computation.

Deformation of log-likelihood loss function for multiclass boosting

Takafumi Kanamori, T. Kanamori, 2010, Neural Networks.

Multiclass Boosting Algorithms for Shrinkage Estimators of Class Probability

Takafumi Kanamori, T. Kanamori, 2007, IEICE Trans. Inf. Syst..

A Density-ratio Framework for Statistical Data Processing

Takafumi Kanamori, Liwei Wang, Masashi Sugiyama, 2009, IPSJ Trans. Comput. Vis. Appl..

Conditional Density Estimation via Least-Squares Density Ratio Estimation

Takafumi Kanamori, Masashi Sugiyama, Taiji Suzuki, 2010, AISTATS.

Direct density-ratio estimation with dimensionality reduction via least-squares hetero-distributional subspace search

Motoaki Kawanabe, Takafumi Kanamori, Masashi Sugiyama, 2011, Neural Networks.

Model Description of Similarity-Based Recommendation Systems

Takafumi Kanamori, Naoya Osugi, T. Kanamori, 2019, Entropy.

Numerical study of reciprocal recommendation with domain matching

T. Kanamori, Naoya Osugi, Kotaro Sudo, 2019, Japanese Journal of Statistics and Data Science.

Non-convex Optimization on Stiefel Manifold and Applications to Machine Learning

Takafumi Kanamori, Akiko Takeda, T. Kanamori, 2012, ICONIP.

Scale-Invariant Divergences for Density Functions

Takafumi Kanamori, T. Kanamori, 2014, Entropy.

Statistical Analysis of Distance Estimators with Density Differences and Density Ratios

Takafumi Kanamori, Masashi Sugiyama, Masashi Sugiyama, 2014, Entropy.

Learning Domain Invariant Representations by Joint Wasserstein Distance Minimization

K. Müller, G. Montavon, T. Kanamori, 2021, Neural Networks.

Direct Divergence Approximation between Probability Distributions and Its Applications in Machine Learning

Takafumi Kanamori, Masashi Sugiyama, Taiji Suzuki, 2013, J. Comput. Sci. Eng..

Constrained Least-Squares Density-Difference Estimation

Takafumi Kanamori, Masashi Sugiyama, Marthinus Christoffel du Plessis, 2013, IEICE Trans. Inf. Syst..

Fisher Efficient Inference of Intractable Models

Takafumi Kanamori, Wittawat Jitkrittum, Yu Chen, 2018, NeurIPS.

Deep Clustering With a Constraint for Topological Invariance Based on Symmetric InfoNCE

T. Kanamori, Yuichiro Wada, Yuhui Zhang, 2023, Neural Computation.

A robust approach based on conditional value-at-risk measure to statistical learning problems

Takafumi Kanamori, Akiko Takeda, T. Kanamori, 2009, Eur. J. Oper. Res..

Statistical models and learning algorithms for ordinal regression problems

Takafumi Kanamori, T. Kanamori, 2013, Inf. Fusion.

Density-Difference Estimation

Masashi Sugiyama, Taiji Suzuki, I. Takeuchi, 2012, Neural Computation.

Density Ratio Estimation in Machine Learning

Masashi Sugiyama, Taiji Suzuki, T. Kanamori, 2012 .

The Entire Solution Path of Kernel-based Nonparametric Conditional Quantile Estimator

Takafumi Kanamori, Ichiro Takeuchi, Kaname Nomura, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

Nonparametric Conditional Density Estimation Using Piecewise-Linear Solution Path of Kernel Quantile Regression

Takafumi Kanamori, Ichiro Takeuchi, Kaname Nomura, 2009, Neural Computation.

Robust modal regression with direct log-density derivative estimation pdf

Tomoya Sakai, Takafumi Kanamori, Hiroaki Sasaki, 2019, ArXiv.

Mode-Seeking Clustering and Density Ridge Estimation via Direct Estimation of Density-Derivative-Ratios

Gang Niu, Takafumi Kanamori, Aapo Hyvärinen, 2017, J. Mach. Learn. Res..

Robust modal regression with direct gradient approximation of modal regression risk

Tomoya Sakai, Takafumi Kanamori, Hiroaki Sasaki, 2020, UAI.

Denoising Cosine Similarity: A Theory-Driven Approach for Efficient Representation Learning

T. Kanamori, K. Takanashi, Takumi Nakagawa, 2023, Neural Networks.

Semi-supervised learning with density-ratio estimation

Takafumi Kanamori, Masanori Kawakita, T. Kanamori, 2012, Machine Learning.

Machine Learning in Non-Stationary Environments - Introduction to Covariate Shift Adaptation

Motoaki Kawanabe, Masashi Sugiyama, M. Kawanabe, 2012, Adaptive computation and machine learning.

Multiscale Bagging and Its Applications

Takafumi Kanamori, Hidetoshi Shimodaira, Masayoshi Aoki, 2011, IEICE Trans. Inf. Syst..