Takafumi Kanamori

According to our database1, Takafumi Kanamori authored at least 62 papers between 2002 and 2017.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.



In proceedings 
PhD thesis 


On csauthors.net:


Graph-based composite local Bregman divergences on discrete sample spaces.
Neural Networks, 2017

Robustness of learning algorithms using hinge loss with outlier indicators.
Neural Networks, 2017

DC Algorithm for Extended Robust Support Vector Machine.
Neural Computation, 2017

Statistical Inference with Unnormalized Discrete Models and Localized Homogeneous Divergences.
Journal of Machine Learning Research, 2017

Mode-Seeking Clustering and Density Ridge Estimation via Direct Estimation of Density-Derivative-Ratios.
Journal of Machine Learning Research, 2017

Parallel distributed block coordinate descent methods based on pairwise comparison oracle.
J. Global Optimization, 2017

Breakdown Point of Robust Support Vector Machines.
Entropy, 2017

Estimating Density Ridges by Direct Estimation of Density-Derivative-Ratios.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

Efficiency Bound of Local Z-Estimators on Discrete Sample Spaces.
Entropy, 2016

Empirical Localization of Homogeneous Divergences on Discrete Sample Spaces.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Using financial risk measures for analyzing generalization performance of machine learning models.
Neural Networks, 2014

Extended Robust Support Vector Machine Based on Financial Risk Minimization.
Neural Computation, 2014

Constrained Least-Squares Density-Difference Estimation.
IEICE Transactions, 2014

Statistical Analysis of Distance Estimators with Density Differences and Density Ratios.
Entropy, 2014

Scale-Invariant Divergences for Density Functions.
Entropy, 2014

Numerical study of learning algorithms on Stiefel manifold.
Comput. Manag. Science, 2014

A Bregman extension of quasi-Newton updates I: an information geometrical framework.
Optimization Methods and Software, 2013

A Unified Classification Model Based on Robust Optimization.
Neural Computation, 2013

Semi-supervised learning with density-ratio estimation.
Machine Learning, 2013

Computational complexity of kernel-based density-ratio estimation: a condition number analysis.
Machine Learning, 2013

Conjugate relation between loss functions and uncertainty sets in classification problems.
Journal of Machine Learning Research, 2013

Direct Divergence Approximation between Probability Distributions and Its Applications in Machine Learning.
JCSE, 2013

A Bregman extension of quasi-Newton updates II: Analysis of robustness properties.
J. Computational Applied Mathematics, 2013

Improving Logitboost with prior knowledge.
Information Fusion, 2013

Statistical models and learning algorithms for ordinal regression problems.
Information Fusion, 2013

f-Divergence Estimation and Two-Sample Homogeneity Test Under Semiparametric Density-Ratio Models.
IEEE Trans. Information Theory, 2012

Statistical analysis of kernel-based least-squares density-ratio estimation.
Machine Learning, 2012

Worst-Case Violation of Sampled Convex Programs for Optimization with Uncertainty.
J. Optimization Theory and Applications, 2012

A Conjugate Property between Loss Functions and Uncertainty Sets in Classification Problems.
Proceedings of the COLT 2012, 2012

Density-Difference Estimation.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Non-convex Optimization on Stiefel Manifold and Applications to Machine Learning.
Proceedings of the Neural Information Processing - 19th International Conference, 2012

A Unified Robust Classification Model.
Proceedings of the 29th International Conference on Machine Learning, 2012

Density Ratio Estimation in Machine Learning.
Cambridge University Press, ISBN: 978-0-521-19017-6, 2012

Direct density-ratio estimation with dimensionality reduction via least-squares hetero-distributional subspace search.
Neural Networks, 2011

Least-squares two-sample test.
Neural Networks, 2011

Statistical outlier detection using direct density ratio estimation.
Knowl. Inf. Syst., 2011

Multiscale Bagging and Its Applications.
IEICE Transactions, 2011

Relative Density-Ratio Estimation for Robust Distribution Comparison.
Proceedings of the 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, 2011

Deformation of log-likelihood loss function for multiclass boosting.
Neural Networks, 2010

Conditional Density Estimation via Least-Squares Density Ratio Estimation.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Least-Squares Conditional Density Estimation.
IEICE Transactions, 2010

Theoretical Analysis of Density Ratio Estimation.
IEICE Transactions, 2010

Direct Density Ratio Estimation with Dimensionality Reduction.
Proceedings of the SIAM International Conference on Data Mining, 2010

Nonparametric Conditional Density Estimation Using Piecewise-Linear Solution Path of Kernel Quantile Regression.
Neural Computation, 2009

A Least-squares Approach to Direct Importance Estimation.
Journal of Machine Learning Research, 2009

A Density-ratio Framework for Statistical Data Processing.
IPSJ Trans. Computer Vision and Applications, 2009

A robust approach based on conditional value-at-risk measure to statistical learning problems.
European Journal of Operational Research, 2009

Mutual information estimation reveals global associations between stimuli and biological processes.
BMC Bioinformatics, 2009

Robust Boosting Algorithm Against Mislabeling in Multiclass Problems.
Neural Computation, 2008

Approximating Mutual Information by Maximum Likelihood Density Ratio Estimation.
Proceedings of the Third Workshop on New Challenges for Feature Selection in Data Mining and Knowledge Discovery, 2008

Efficient Direct Density Ratio Estimation for Non-stationarity Adaptation and Outlier Detection.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Inlier-Based Outlier Detection via Direct Density Ratio Estimation.
Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

Robust Loss Functions for Boosting.
Neural Computation, 2007

Pool-based active learning with optimal sampling distribution and its information geometrical interpretation.
Neurocomputing, 2007

Multiclass Boosting Algorithms for Shrinkage Estimators of Class Probability.
Proceedings of the Algorithmic Learning Theory, 18th International Conference, 2007

Geometrical Structure of Boosting Algorithm.
New Generation Comput., 2006

Conditional mean estimation under asymmetric and heteroscedastic error by linear combination of quantile regressions.
Computational Statistics & Data Analysis, 2006

The Entire Solution Path of Kernel-based Nonparametric Conditional Quantile Estimator.
Proceedings of the International Joint Conference on Neural Networks, 2006

Information Geometry of U-Boost and Bregman Divergence.
Neural Computation, 2004

The Most Robust Loss Function for Boosting.
Proceedings of the Neural Information Processing, 11th International Conference, 2004

Robust Regression with Asymmetric Heavy-Tail Noise Distributions.
Neural Computation, 2002

A New Sequential Algorithm for Regression Problems by Using Mixture Distribution.
Proceedings of the Artificial Neural Networks, 2002