Learning domain invariant representations by joint Wasserstein distance minimization Reviewed International coauthorship

Léo Andéol, Yusei Kawakami, Yuichiro Wada, Takafumi Kanamori, Klaus-Robert Müller, Grégoire Montavon

Neural Networks   167   233 - 243   2023.10

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

Yuhui Zhang, Yuichiro Wada, Hiroki Waida, Kaito Goto, Yusaku Hino, Takafumi Kanamori

Neural Computation   35 ( 7 )   1288 - 1339   2023.7

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

Takumi Nakagawa, Yutaro Sanada, Hiroki Waida, Yuhui Zhang, Yuichiro Wada, Kosaku Takanashi, Tomonori Yamada, Takafumi Kanamori

CoRR   abs/2304.09552   2023

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

Hiroki Waida, Yuichiro Wada, Léo Andéol, Takumi Nakagawa, Yuhui Zhang, Takafumi Kanamori

CoRR   abs/2304.00395   2023

Deep Clustering with a Constraint for Topological Invariance based on Symmetric InfoNCE.

Yuhui Zhang, Yuichiro Wada, Hiroki Waida, Kaito Goto, Yusaku Hino, Takafumi Kanamori

CoRR   abs/2303.03036   2023

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

Hiroki Waida, Yuichiro Wada, Léo Andéol, Takumi Nakagawa, Yuhui Zhang, Takafumi Kanamori

Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference   709 - 727   2023

A Convex Framework for Confounding Robust Inference.

Kei Ishikawa, Niao He, Takafumi Kanamori

CoRR   abs/2309.12450   2023

Deep Self-Supervised Learning of Speech Denoising from Noisy Speeches. Reviewed

Yutaro Sanada, Takumi Nakagawa, Yuichiro Wada, Kosaku Takanashi, Yuhui Zhang, Kiichi Tokuyama, Takafumi Kanamori, Tomonori Yamada

23rd Annual Conference of the International Speech Communication Association(INTERSPEECH)   1178 - 1182   2022

Mode estimation on matrix manifolds: Convergence and robustness. Reviewed

Hiroaki Sasaki, Jun-Ichiro Hirayama, Takafumi Kanamori

International Conference on Artificial Intelligence and Statistics(AISTATS)   8056 - 8079   2022

Estimating Density Models with Truncation Boundaries using Score Matching. Reviewed

Song Liu 0002, Takafumi Kanamori, Daniel J. Williams

Journal of Machine Learning Research   23   186 - 38   2022

Learning Domain Invariant Representations by Joint Wasserstein Distance Minimization.

Léo Andéol, Yusei Kawakami, Yuichiro Wada, Takafumi Kanamori, Klaus-Robert Müller, Grégoire Montavon

CoRR   abs/2106.04923   2021

Uncertainty propagation for dropout-based Bayesian neural networks. Reviewed

Yuki Mae, Wataru Kumagai, Takafumi Kanamori

Neural Networks   144   394 - 406   2021

Robust modal regression with direct gradient approximation of modal regression risk. Reviewed

Hiroaki Sasaki, Tomoya Sakai, Takafumi Kanamori

Conference on Uncertainty in Artificial Intelligence (UAI),   380 - 389   2020

A Unified Statistically Efficient Estimation Framework for Unnormalized Models. Reviewed

Masatoshi Uehara, Takafumi Kanamori, Takashi Takenouchi, Takeru Matsuda

The 23rd International Conference on Artificial Intelligence and Statistics(AISTATS)   809 - 819   2020

東京工業大学情報理工学院数理・計算科学系―情報の未来を作り出す数理的アプローチを探究する― Reviewed

金森敬文, 樺島祥介, 高安美佐子, 中野 張, 福田光浩, 三好直人, 山下 真, 渡邊澄夫

オペレーションズ・リサーチ   2019.1

Robust modal regression with direct log-density derivative estimation.

Hiroaki Sasaki, Tomoya Sakai 0001, Takafumi Kanamori

CoRR   abs/1910.08280   2019

Unified estimation framework for unnormalized models with statistical efficiency. Reviewed

Masatoshi Uehara, Takafumi Kanamori, Takashi Takenouchi, Takeru Matsuda

CoRR   abs/1901.07710   2019

Model Description of Similarity-Based Recommendation Systems. Reviewed

Takafumi Kanamori, Naoya Osugi

Entropy   21 ( 7 )   702 - 702   2019

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

Yuichiro Wada, Siqiang Su, Wataru Kumagai, Takafumi Kanamori

IEICE Transactions on Information & Systems   102-D ( 8 )   1537 - 1545   2019

Spectral Embedded Deep Clustering. Reviewed

Yuichiro Wada, Shugo Miyamoto, Takumi Nakagama, Léo Andéol, Wataru Kumagai, Takafumi Kanamori

Entropy   21 ( 8 )   795 - 795   2019

Estimating Density Models with Complex Truncation Boundaries.

Song Liu 0002, Takafumi Kanamori

CoRR   abs/1910.03834   2019

Fisher Efficient Inference of Intractable Models. Reviewed

Song Liu 0002, Takafumi Kanamori, Wittawat Jitkrittum, Yu Chen

Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019(NeurIPS)   8790 - 8800   2019

Variable Selection for Nonparametric Learning with Power Series Kernels. Reviewed

Kota Matsui, Wataru Kumagai, Kenta Kanamori, Mitsuaki Nishikimi, Takafumi Kanamori

Neural Computation   31 ( 8 )   1718 - 1750   2019

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

Wataru Kumagai, Takafumi Kanamori

Machine Learning   108 ( 11 )   1975 - 2008   2019

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

Takafumi Kanamori, Takashi Takenouchi

NEURAL NETWORKS   95   44 - 56   2017.11

Parallel distributed block coordinate descent methods based on pairwise comparison oracle Reviewed

Kota Matsui, Wataru Kumagai, Takafumi Kanamori

JOURNAL OF GLOBAL OPTIMIZATION   69 ( 1 )   1 - 21   2017.9

Breakdown Point of Robust Support Vector Machines. Reviewed

Takafumi Kanamori, Shuhei Fujiwara, Akiko Takeda

Entropy   19 ( 2 )   83 - 83   2017

Robustness of learning algorithms using hinge loss with outlier indicators. Reviewed

Takafumi Kanamori, Shuhei Fujiwara, Akiko Takeda

Neural Networks   94   173 - 191   2017

Statistical Inference with Unnormalized Discrete Models and Localized Homogeneous Divergences Reviewed

Takashi Takenouchi, Takafumi Kanamori

JOURNAL OF MACHINE LEARNING RESEARCH   18   1 - 26   2017

DC Algorithm for Extended Robust Support Vector Machine. Reviewed

Shuhei Fujiwara, Akiko Takeda, Takafumi Kanamori

Neural Computation   29 ( 5 )   1406 - 1438   2017

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

Hiroaki Sasaki, Takafumi Kanamori, Aapo Hyvärinen, Gang Niu 0001, Masashi Sugiyama

J. Mach. Learn. Res.   18   180 - 47   2017

Estimating density ridges by direct estimation of density-derivative-ratios Reviewed

Hiroaki Sasaki, Takafumi Kanamori, Masashi Sugiyama

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, AISTATS 2017   54   204 - 212   2017

Efficiency Bound of Local Z-Estimators on Discrete Sample Spaces Reviewed

Takafumi Kanamori

ENTROPY   18 ( 7 )   273 - 273   2016.7

Robustification of Learning Algorithms using Hinge-loss (情報論的学習理論と機械学習 情報論的学習理論ワークショップ(IBIS2015))

Kanamori Takafumi, Fujiwara Shuhei, Takeda Akiko

電子情報通信学会技術研究報告 = IEICE technical report : 信学技報   115 ( 323 )   139 - 146   2015.11

Robust estimation under heavy contamination using unnormalized models Reviewed

Takafumi Kanamori, Hironori Fujisawa

BIOMETRIKA   102 ( 3 )   559 - 572   2015.9

Empirical Localization of Homogeneous Divergences on Discrete Sample Spaces. Reviewed

Takashi Takenouchi, Takafumi Kanamori

Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, December 7-12, 2015, Montreal, Quebec, Canada   820 - 828   2015

Breakdown Point of Robust Support Vector Machine

Kanamori Takafumi, Fujiwara Shuhei, Takeda Akiko

CoRR   114 ( 306 )   49 - 56   2014.11

Extended Robust Support Vector Machine Based on Financial Risk Minimization Reviewed

Akiko Takeda, Shuhei Fujiwara, Takafumi Kanamori

NEURAL COMPUTATION   26 ( 11 )   2541 - 2569   2014.11

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

Takafumi Kanamori, Hironori Fujisawa

BERNOULLI   20 ( 4 )   2278 - 2304   2014.11

Numerical study of learning algorithms on Stiefel manifold Reviewed

Takafumi Kanamori, Akiko Takeda

Computational Management Science   11 ( 4 )   319 - 340   2014.9

アフィン不変ダイバージェンスとその応用 (統計多様体の幾何学の新展開)

金森 敬文, 藤澤 洋徳

数理解析研究所講究録   1916   213 - 224   2014.9

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

Takeda, Akiko, Kanamori, Takafumi

NEURAL NETWORKS   57   29 - 38   2014.9

Constrained Least-Squares Density-Difference Estimation Reviewed

Tuan Duong Nguyen, Marthinus Christoffel Du Plessis, Takafumi Kanamori, Masashi Sugiyama

IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS   E97D ( 7 )   1822 - 1829   2014.7

Scale-Invariant Divergences for Density Functions Reviewed

Takafumi Kanamori

ENTROPY   16 ( 5 )   2611 - 2628   2014.5

Statistical Analysis of Distance Estimators with Density Differences and Density Ratios Reviewed

Takafumi Kanamori, Masashi Sugiyama

ENTROPY   16 ( 2 )   921 - 942   2014.2

Parallel Distributed Block Coordinate Descent Methods based on Pairwise Comparison Oracle.

Kota Matsui, Wataru Kumagai, Takafumi Kanamori

CoRR   abs/1409.3912   2014

Density-Difference Estimation Reviewed

Masashi Sugiyama, Takafumi Kanamori, Taiji Suzuki, Marthinus Christoffel du Plessis, Song Liu, Ichiro Takeuchi

NEURAL COMPUTATION   25 ( 10 )   2734 - 2775   2013.10

Conjugate Relation between Loss Functions and Uncertainty Sets in Classification Problems Reviewed

Takafumi Kanamori, Akiko Takeda, Taiji Suzuki

JOURNAL OF MACHINE LEARNING RESEARCH   14 ( 1 )   1461 - 1504   2013.6

Semi-supervised learning with density-ratio estimation Reviewed

Masanori Kawakita, Takafumi Kanamori

MACHINE LEARNING   91 ( 2 )   189 - 209   2013.5

Statistical models and learning algorithms for ordinal regression problems Reviewed

Takafumi Kanamori

INFORMATION FUSION   14 ( 2 )   199 - 207   2013.4

2-A-1 金融リスク指標に基づく外れ値に対して頑健なサポートベクターマシンの拡張(OR一般(2))

藤原 秀平, 武田 朗子, 金森 敬文

日本オペレーションズ・リサーチ学会春季研究発表会アブストラクト集   2013   122 - 123   2013.3

A Unified Classification Model Based on Robust Optimization Reviewed

Akiko Takeda, Hiroyuki Mitsugi, Takafumi Kanamori

NEURAL COMPUTATION   25 ( 3 )   759 - 804   2013.3

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

Takafumi Kanamori, Taiji Suzuki, Masashi Sugiyama

MACHINE LEARNING   90 ( 3 )   431 - 460   2013.3

A Bregman Extension of quasi-Newton updates I: An Information Geometrical framework Reviewed

T. Kanamori, A. Ohara

Optimization Methods and Software   28 ( 1 )   96-123 - 123   2013.2

Improving Logitboost with prior knowledge Reviewed

Takafumi Kanamori, Takashi Takenouchi

Information Fusion   14 ( 2 )   208 - 219   2013

Relative Density-Ratio Estimation for Robust Distribution Comparison. Reviewed

Makoto Yamada, Taiji Suzuki, Takafumi Kanamori, Hirotaka Hachiya, Masashi Sugiyama

Neural Computation   25 ( 5 )   1324 - 1370   2013

Direct divergence approximation between probability distributions and its applications in machine learning Reviewed

Masashi Sugiyama, Song Liu, Marthinus Christoffel du Plessis, Masao Yamanaka, Makoto Yamada, Taiji Suzuki, Takafumi Kanamori

Journal of Computing Science and Engineering   7 ( 2 )   99 - 111   2013

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

Takafumi Kanamori, Atsumi Ohara

Journal of Computational and Applied Mathematics   253   104 - 122   2013

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

Masashi Sugiyama, Taiji Suzuki, Takafumi Kanamori

ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS   64 ( 5 )   1009 - 1044   2012.10

A Unified Robust Classification Model Reviewed

Takeda, A, Mitsugi, H, Kanamori, T

29th International Conference on Machine Learning   abs/1206.4599   2012.6

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

Kanamori, T, Takeda, A, Suzuki, T

25th International Conference on Learning Theory   abs/1204.6583   29.1-29.23 - 23   2012.6

Pooling design and bias correction in DNA library screening Reviewed

Takafumi Kanamori, Hiroaki Uehara, Masakazu Jimbo

Journal of Statistical Theory and Practice   6 ( 1 )   220 - 238   2012.3

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

Takafumi Kanamori, Taiji Suzuki, Masashi Sugiyama

MACHINE LEARNING   86 ( 3 )   335 - 367   2012.3

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

Takafumi Kanamori, Taiji Suzuki, Masashi Sugiyama

IEEE TRANSACTIONS ON INFORMATION THEORY   58 ( 2 )   708 - 720   2012.2

Density ratio estimation in machine learning

Masashi Sugiyama, Taiji Suzuki, Takafumi Kanamori

Density Ratio Estimation in Machine Learning   9780521190176   1 - 329   2012.1

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

Takafumi Kanamori, Akiko Takeda

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS   152 ( 1 )   171 - 197   2012.1

Density-Difference Estimation

Masashi Sugiyama, Takafumi Kanamori, Taiji Suzuki, Marthinus Christoffel du Plessis, Song Liu 0002, Ichiro Takeuchi

CoRR   abs/1207.0099   2012

Density-difference estimation Reviewed

Masashi Sugiyama, Takafumi Kanamori, Taiji Suzuki, Marthinus Christoffel Du Plessis, Song Liu, Ichiro Takeuchi

Advances in Neural Information Processing Systems   1   683 - 691   2012

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

Takafumi Kanamori, Akiko Takeda

NEURAL INFORMATION PROCESSING, ICONIP 2012, PT I   7663   109 - 116   2012

Multiscale Bagging and Its Applications Reviewed

Hidetoshi Shimodaira, Takafumi Kanamori, Masayoshi Aoki, Kouta Mine

IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS   E94D ( 10 )   1924 - 1932   2011.10

Least-squares two-sample test Reviewed

Masashi Sugiyama, Taiji Suzuki, Yuta Itoh, Takafumi Kanamori, Manabu Kimura

NEURAL NETWORKS   24 ( 7 )   735 - 751   2011.9

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

Masashi Sugiyama, Makoto Yamada, Paul von Buenau, Taiji Suzuki, Takafumi Kanamori, Motoaki Kawanabe

NEURAL NETWORKS   24 ( 2 )   183 - 198   2011.3

Statistical outlier detection using direct density ratio estimation Reviewed

Shohei Hido, Yuta Tsuboi, Hisashi Kashima, Masashi Sugiyama, Takafumi Kanamori

KNOWLEDGE AND INFORMATION SYSTEMS   26 ( 2 )   309 - 336   2011.2

Relative Density-Ratio Estimation for Robust Distribution Comparison.

Makoto Yamada, Taiji Suzuki, Takafumi Kanamori, Hirotaka Hachiya, Masashi Sugiyama

Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011(NIPS)   594 - 602   2011

Deformation of log-likelihood loss function for multiclass boosting Reviewed

Takafumi Kanamori

NEURAL NETWORKS   23 ( 7 )   843 - 864   2010.9

A Bregman extension of quasi-Newton updates

Kanamori T, Ohara Atsumi

Proceedings of the third conference on Information Geometry and its Applications   IGAIA2010   30   2010.8

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

Sugiyama Masashi, Suzuki Taiji, Kanamori Takafumi

RIMS Kokyuroku   ( 1703 )   10 - 31   2010.8

Theoretical Analysis of Density Ratio Estimation Reviewed

Takafumi Kanamori, Taiji Suzuki, Masashi Sugiyama

IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E93A ( 4 )   787 - 798   2010.4

Least-Squares Conditional Density Estimation Reviewed

Masashi Sugiyama, Ichiro Takeuchi, Taiji Suzuki, Takafumi Kanamori, Hirotaka Hachiya, Daisuke Okanohara

IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS   E93D ( 3 )   583 - 594   2010.3

Direct density ratio estimation with dimensionality reduction Reviewed

Masashi Sugiyama, Satoshi Hara, Paul Von Bünau, Taiji Suzuki, Takafumi Kanamori, Motoaki Kawanabe

Proceedings of the 10th SIAM International Conference on Data Mining, SDM 2010   SIAM International Conference   595 - 606   2010

Conditional density estimation via least-squares density ratio estimation Reviewed

Masashi Sugiyama, Ichiro Takeuchi, Taiji Suzuki, Takafumi Kanamori, Hirotaka Hachiya, Daisuke Okanohara

Journal of Machine Learning Research   9   781 - 788   2010

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

Akiko Takeda, Takafumi Kanamori

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH   198 ( 1 )   287 - 296   2009.10

A Least-squares Approach to Direct Importance Estimation Reviewed

Takafumi Kanamori, Shohei Hido, Masashi Sugiyama

JOURNAL OF MACHINE LEARNING RESEARCH   10   1391 - 1445   2009.7

Condition Number Analysis of Kernel-based Density Ratio Estimation Reviewed

T. Kanamori, T. Suzuki, M. Sugiyama

ICML workshop on Numerical Mathematics in Machine Learning   ICML workshop 2009   2009.6

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

Ichiro Takeuchi, Kaname Nomura, Takafumi Kanamori

NEURAL COMPUTATION   21 ( 2 )   533 - 559   2009.2

Mutual information estimation reveals global associations between stimuli and biological processes Reviewed

Taiji Suzuki, Masashi Sugiyama, Takafumi Kanamori, Jun Sese

BMC BIOINFORMATICS   10 ( 1 )   S52   2009.1

A density-ratio framework for statistical data processing Reviewed

Masashi Sugiyama, Takafumi Kanamori, Taiji Suzuki, Shohei Hido, Jun Sese, Ichiro Takeuchi, Liwei Wang

IPSJ Transactions on Computer Vision and Applications   1   183 - 208   2009

A Density-ratio Framework for Statistical Data Processing

Sugiyama Masashi, Kanamori Takafumi, Suzuki Taiji, Hido Shohei, Sese Jun, Takeuchi Ichiro, Wang Liwei

Information and Media Technologies   4 ( 4 )   962 - 987   2009

Efficient direct density ratio estimation for non-stationarity adaptation and outlier detection Reviewed

Takafumi Kanamori, Shohei Hido, Masashi Sugiyama

Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference   NIPS2008   809 - 816   2009

Robust boosting algorithm against mislabeling in multiclass problems Reviewed

Takashi Takenouchi, Shinto Eguchi, Noboru Murata, Takafumi Kanamori

NEURAL COMPUTATION   20 ( 6 )   1596 - 1630   2008.6

Approximating mutual information by maximum likelihood density ratio estimation Reviewed

Suzuki Taiji, Sugiyama Masashi, Sese Jun, Kanamori Takafumi

New challenges for feature selection in data mining and knowledge discovery   5 - 20   2008

Inlier-based Outlier Detection via Direct Density Ratio Estimation Reviewed

Shohei Hido, Yuta Tsuboi, Hisashi Kashima, Masashi Sugiyama, Takafumi Kanamori

ICDM 2008: EIGHTH IEEE INTERNATIONAL CONFERENCE ON DATA MINING, PROCEEDINGS   ICDM2008   223 - 232   2008

A least-squares approach to mutual information estimation with application in variable selection Reviewed

Taiji Suzuki, Masashi Sugiyama, Jun Sese, Takafumi Kanamori

Proceedings of Workshop on New Challenges for Feature Selection in Data Mining and Knowledge Discoverty   FSDM2008   362-367   2008

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

Takafumi Kanamori

NEUROCOMPUTING   71 ( 1-3 )   353 - 362   2007.12

Multiclass boosting algorithms for shrinkage estimators of class probability Reviewed

Takafumi Kanamori

IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS   E90D ( 12 )   2033 - 2042   2007.12

Robust loss functions for boosting Reviewed

Takafumi Kanamori, Takashi Takenouchi, Shinto Eguchi, Noboru Murata

NEURAL COMPUTATION   19 ( 8 )   2183 - 2244   2007.8

Multiclass boosting algorithms for shrinkage estimators of class probability Reviewed

Takafumi Kanamori

Algorithmic Learning Theory, Proceedings   4754   358 - 372   2007

Tutorial series on brain-inspired computing Part 6: Geometrical structure of boosting algorithm Invited Reviewed

Takafumi Kanamori, Takashi Takenouchi, Noboru Murata

NEW GENERATION COMPUTING   25 ( 1 )   117 - 141   2007

2-E-3 ロバスト最適化問題に対する確率的解法の精度評価(非線形最適化)

武田 朗子, 金森 敬文, 田口 俊介, 田中 努

日本オペレーションズ・リサーチ学会秋季研究発表会アブストラクト集   2006   254 - 255   2006.9

Conditional mean estimation under asymmetric and heteroscedastic error by linear combination of quantile regressions Reviewed

T Kanamori, Takeuchi, I

COMPUTATIONAL STATISTICS & DATA ANALYSIS   50 ( 12 )   3605 - 3618   2006.8

The entire solution path of kernel-based nonparametric conditional quantile estimator Reviewed

Ichiro Takeuchi, Kaname Nomura, Takafumi Kanamori

2006 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORK PROCEEDINGS, VOLS 1-10   IJCNN2006   153 - +   2006

Integrability of weak learner on boosting

T. Kanamori

Proceedings of the 2nd International Symposium on Information Geometry and its Applications   IGAIA 2005   2005

Robust Boosting and Loss Functions

KANAMORI Takafumi, TAKENOUCHI Takashi, EGUCHI Shinto, MURATA Noboru

IEICE technical report. Neurocomputing   104 ( 225 )   1 - 6   2004.7

Information geometry of U-Boost and Bregman divergence Reviewed

N Murata, T Takenouchi, T Kanamori, S Eguchi

NEURAL COMPUTATION   16 ( 7 )   1437 - 1481   2004.7

The most robust loss function for boosting Reviewed

T Kanamori, T Takenouchi, S Eguchi, N Murata

NEURAL INFORMATION PROCESSING   3316   496 - 501   2004

Boosting and Its Robustness

KANAMORI Takafumi, MURATA Noboru

The Journal of the Institute of Electronics, Information and Communication Engineers   86 ( 10 )   769 - 772   2003.10

Active learning algorithm using the maximum weighted log-likelihood estimator Reviewed

T Kanamori, H Shimodaira

JOURNAL OF STATISTICAL PLANNING AND INFERENCE   116 ( 1 )   149 - 162   2003.9

Robust regression with asymmetric heavy-tail noise distributions Reviewed

Takeuchi, I, Y Bengio, T Kanamori

NEURAL COMPUTATION   14 ( 10 )   2469 - 2496   2002.10

Statistical asymptotic theory of active learning Reviewed

T Kanamori

ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS   54 ( 3 )   459 - 475   2002.9

A new sequential algorithm for regression problems by using mixture distribution Reviewed

T Kanamori

ARTIFICIAL NEURAL NETWORKS - ICANN 2002   2415   535 - 540   2002

An Active Learning Algorithm Using an Information Criterion for the Maximum Weighted Log-likelihood Estimator. Reviewed

T. Kanamori, H. Shimodaira

Proceedings of the Institute of Statistical Mathematics   48 ( 1 )   197-212   2000

重み付き最尤推定量の情報量規準を用いた能動学習アルゴリズムの提案

金森 敬文, 下平 英寿

統計数理   48 ( 1 )   197 - 212   2000

Adaptive algorithm for active learning using an information criterion for the maximum weighted log-likelihood estimator.

金森敬文, 下平英寿

電子情報通信学会技術研究報告   99 ( 131(NC99 11-28) )   1999

Active Learning Algorithm using Maximum Weighted Likelihood Estimator. Reviewed

T. Kanamori

11 ( 2 )   65-75   1998

統計的学習理論

金森敬文（ Role： Sole author）

講談社  2015.4 

モンテカルロ法ハンドブック

伏見正則（ Role： Joint author）

朝倉書店  2014.10 

統計的学習の基礎 ―データマイニング・推論・予測―

Trevor Hastie, Robert Tibshirani, Jerome Friedman, 杉山 将, 井手 剛, 神嶌 敏弘, 栗田 多喜夫, 前田 英作, 井尻 善久, 岩田 具治, 金森 敬文, 兼村 厚範, 烏山 昌幸, 河原 吉伸, 木村 昭悟, 小西 嘉典, 酒井 智弥, 鈴木 大慈, 竹内 一郎, 玉木 徹, 出口 大輔, 冨岡 亮太, 波部 斉, 前田 新一, 持橋 大地, 山田 誠（ Role： Joint author）

共立出版  2014.6 

応用数理ハンドブック

薩摩順吉, 大石進一, 杉原正顕（ Role： Joint author）

朝倉書店  2013.11 

Density Ratio Estimation in Machine Learning

Masashi Sugiyama, Taiji Suzuki, Takafumi Kanamori（ Role： Joint author）

Cambridge University Press  2012.3 

Encyclopedia of Mathematical Engineering

（ Role： Joint author）

2011.11 

Pattern Recognition with R

（ Role： Joint author）

2009.10 

Geometry of Covariate Shift with Applications to Active Learning,

T. Kanamori, H. Shimodaira（ Role： Joint author）

MIT Press  2008 

Boosting -- design of learning algorithms

Takafumi Kanamori, Kohei Hatano, Osamu Watanabe（ Role： Joint author）

Morikita Publishing Co.  2006.9 

Integrability of weak learner on boosting

The 2nd International Symposium on Information Geometry and its Applications  2005.12 

A Unified Robust Classification Model

Takeda, A, Mitsugi, H, Kanamori, T

29th International Conference on Machine Learning  2012.6 

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

Kanamori, T, Takeda, A, Suzuki, T

25th International Conference on Learning Theory  2012.6 

Condition Number Analysis of Kernel-based Density Ratio Estimation

T. Kanamori, T. Suzuki, M. Sugiyama

ICML workshop on Numerical Mathematics in Machine Learning  2009.6 

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

Kanamori T, Takeda A

The 19th International Conference on Neural Information Processing  2012.11 

２値判別における損失関数と不確実性集合の共役性 International conference

金森敬文, 武田朗子, 鈴木大慈

統計関連学会連合大会  2012.9 

Robust optimization-based classification method.

Takeda A, Kanamori T, Mitsugi H

The 21st International Symposium on Mathematical Programming  2012.8 

f-divergence estimation and two-sample test under semi-parametric density ratio models.

Kanamori T, Suzuki, T, Sugiyama, M

The 2nd Institute of Mathematical Statistics, Asia Pacific Rim Meeting  2012.7 

アファイン不変なダイバージェンスとそのロバスト統計への応用 International conference

金森敬文

ミニワークショップ 統計多様体の幾何学とその周辺 (4)  2013.3 

Affine Invariant Divergences for Robust Statistical Inference International conference

SITA2012  2012.12 

Density-Difference Estimation.

Sugiyama M, Kanamori T, Suzuki T, Plessis M, Liu S, Takeuchi I

The Neural Information Processing Systems  2012.12 

アファイン不変な統計的ダイバージェンスとその応用 International conference

金森敬文

統計数理研究所 共同利用「確率測度の最適化と通信路容量」  2013.3 

Random Fuzzy Multiobjective Linear Programming Through Probability Maximization

Hitoshi Yano, Kota Matsui

International MultiConference of Engineers and Computer Scientists 2013,  2013.3 

アファイン不変なダイバージェンスとその応用 International conference

金森敬文

情報幾何と関連分野 小研究集会  2013.3 

Constrained Least-Squares Density-Difference Estimation

Nguyen Tuan Duong, Marthinus Christoffel du Plessis, Takafumi Kanamori, Masashi Sugiyama

2013.3 

Affine Invariant Divergences and their Applications

T. Kanamori, H. Fujisawa

The 3rd Institute of Mathematical Statistics, Asia Pacific Rim Meeting  2014.6 

ヘルダー不等式とスケール不変ダイバージェンス International conference

金森敬文

京都大学数理解析研究所短期共同研究 統計多様体の幾何学の新展開  2014.2 

アファイン不変な統計的ダイバージェンスとその応用 International conference

金森敬文, 藤澤洋徳

統計関連学会連合大会  2013.9 

Semi-Supervised learning with Density-Ratio Estimation International conference

2013.3 

Empirical Localization of Homogeneous Divergences on Discrete Sample Spaces

Takashi Takenouchi, Takafumi Kanamori

The Neural Information Processing Systems  2015.12