Masashi Sugiyama

According to our database1, Masashi Sugiyama
  • authored at least 322 papers between 1999 and 2017.
  • has a "Dijkstra number"2 of four.

Timeline

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Bibliography

2017
Direct Estimation of the Derivative of Quadratic Mutual Information with Application in Supervised Dimension Reduction.
Neural Computation, 2017

Homotopy continuation approaches for robust SV classification and regression.
Machine Learning, 2017

Class-prior estimation for learning from positive and unlabeled data.
Machine Learning, 2017

Geometry-aware principal component analysis for symmetric positive definite matrices.
Machine Learning, 2017

Introduction: special issue of selected papers from ACML 2015.
Machine Learning, 2017

Foreword: special issue for the journal track of the 8th Asian conference on machine learning (ACML 2016).
Machine Learning, 2017

Tensor Networks for Dimensionality Reduction and Large-scale Optimization: Part 2 Applications and Future Perspectives.
Foundations and Trends in Machine Learning, 2017

Hierarchical Policy Search via Return-Weighted Density Estimation.
CoRR, 2017

Binary Classification from Positive-Confidence Data.
CoRR, 2017

Estimation of Squared-Loss Mutual Information from Positive and Unlabeled Data.
CoRR, 2017

Learning Efficient Tensor Representations with Ring Structure Networks.
CoRR, 2017

Semi-Supervised AUC Optimization based on Positive-Unlabeled Learning.
CoRR, 2017

Misdirected Registration Uncertainty.
CoRR, 2017

Positive-Unlabeled Learning with Non-Negative Risk Estimator.
CoRR, 2017

Learning from Complementary Labels.
CoRR, 2017

Learning Discrete Representations via Information Maximizing Self Augmented Training.
CoRR, 2017

Risk Minimization Framework for Multiple Instance Learning from Positive and Unlabeled Bags.
CoRR, 2017

Generative Local Metric Learning for Kernel Regression.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Positive-Unlabeled Learning with Non-Negative Risk Estimator.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Learning from Complementary Labels.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Expectation Propagation for t-Exponential Family Using q-Algebra.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Semi-Supervised Classification Based on Classification from Positive and Unlabeled Data.
Proceedings of the 34th International Conference on Machine Learning, 2017

Learning Discrete Representations via Information Maximizing Self-Augmented Training.
Proceedings of the 34th International Conference on Machine Learning, 2017

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

Least-Squares Log-Density Gradient Clustering for Riemannian Manifolds.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

Policy Search with High-Dimensional Context Variables.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Trial and Error: Using Previous Experiences as Simulation Models in Humanoid Motor Learning.
IEEE Robot. Automat. Mag., 2016

Model-based reinforcement learning with dimension reduction.
Neural Networks, 2016

Regularized Multitask Learning for Multidimensional Log-Density Gradient Estimation.
Neural Computation, 2016

Theoretical and Experimental Analyses of Tensor-Based Regression and Classification.
Neural Computation, 2016

Direct Density Derivative Estimation.
Neural Computation, 2016

An Online Policy Gradient Algorithm for Markov Decision Processes with Continuous States and Actions.
Neural Computation, 2016

Computationally Efficient Class-Prior Estimation under Class Balance Change Using Energy Distance.
IEICE Transactions, 2016

Policy Search with High-Dimensional Context Variables.
CoRR, 2016

Beyond the Low-density Separation Principle: A Novel Approach to Semi-supervised Learning.
CoRR, 2016

Class-prior Estimation for Learning from Positive and Unlabeled Data.
CoRR, 2016

Theoretical Comparisons of Learning from Positive-Negative, Positive-Unlabeled, and Negative-Unlabeled Data.
CoRR, 2016

Reinterpreting the Transformation Posterior in Probabilistic Image Registration.
CoRR, 2016

Robust supervised learning under uncertainty in dataset shift.
CoRR, 2016

Geometry-aware stationary subspace analysis.
CoRR, 2016

Dependence maximization localization: a novel approach to 2D street-map-based robot localization.
Advanced Robotics, 2016

Faster Stochastic Variational Inference using Proximal-Gradient Methods with General Divergence Functions.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Semi-supervised sufficient dimension reduction under class-prior change.
Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2016

Theoretical Comparisons of Positive-Unlabeled Learning against Positive-Negative Learning.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Modal Regression via Direct Log-Density Derivative Estimation.
Proceedings of the Neural Information Processing - 23rd International Conference, 2016

Structure Learning of Partitioned Markov Networks.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Target-less camera-LiDAR extrinsic calibration using a bagged dependence estimator.
Proceedings of the IEEE International Conference on Automation Science and Engineering, 2016

Non-Gaussian Component Analysis with Log-Density Gradient Estimation.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Multitask Principal Component Analysis.
Proceedings of The 8th Asian Conference on Machine Learning, 2016

Geometry-aware stationary subspace analysis.
Proceedings of The 8th Asian Conference on Machine Learning, 2016

2015
Active Learning in Recommender Systems.
Proceedings of the Recommender Systems Handbook, 2015

Importance-weighted covariance estimation for robust common spatial pattern.
Pattern Recognition Letters, 2015

Cross-Domain Matching with Squared-Loss Mutual Information.
IEEE Trans. Pattern Anal. Mach. Intell., 2015

Bandit-Based Task Assignment for Heterogeneous Crowdsourcing.
Neural Computation, 2015

Conditional Density Estimation with Dimensionality Reduction via Squared-Loss Conditional Entropy Minimization.
Neural Computation, 2015

Online Direct Density-Ratio Estimation Applied to Inlier-Based Outlier Detection.
Neural Computation, 2015

Direct conditional probability density estimation with sparse feature selection.
Machine Learning, 2015

Introduction: special issue of selected papers of ACML 2013.
Machine Learning, 2015

Condition for perfect dimensionality recovery by variational Bayesian PCA.
Journal of Machine Learning Research, 2015

Direct Density Ratio Estimation with Convolutional Neural Networks with Application in Outlier Detection.
IEICE Transactions, 2015

Task Selection for Bandit-Based Task Assignment in Heterogeneous Crowdsourcing.
CoRR, 2015

Bandit-Based Task Assignment for Heterogeneous Crowdsourcing.
CoRR, 2015

Supervised LogEuclidean Metric Learning for Symmetric Positive Definite Matrices.
CoRR, 2015

Theoretical and Experimental Analyses of Tensor-Based Regression and Classification.
CoRR, 2015

Homotopy Continuation Approaches for Robust SV Classification and Regression.
CoRR, 2015

Online Markov decision processes with policy iteration.
CoRR, 2015

Convergence of Proximal-Gradient Stochastic Variational Inference under Non-Decreasing Step-Size Sequence.
CoRR, 2015

Task selection for bandit-based task assignment in heterogeneous crowdsourcing.
Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2015

Predictive Approaches for Low-Cost Preventive Medicine Program in Developing Countries.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

A dependence maximization approach towards street map-based localization.
Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015

Stroke-Based Stylization Learning and Rendering with Inverse Reinforcement Learning.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Convex Formulation for Learning from Positive and Unlabeled Data.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Minimum dependency key frames selection via quadratic mutual information.
Proceedings of the Tenth International Conference on Digital Information Management, 2015

Averaging covariance matrices for EEG signal classification based on the CSP: An empirical study.
Proceedings of the 23rd European Signal Processing Conference, 2015

Direct Density-Derivative Estimation and Its Application in KL-Divergence Approximation.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Regularized Policy Gradients: Direct Variance Reduction in Policy Gradient Estimation.
Proceedings of The 7th Asian Conference on Machine Learning, 2015

Sufficient Dimension Reduction via Direct Estimation of the Gradients of Logarithmic Conditional Densities.
Proceedings of The 7th Asian Conference on Machine Learning, 2015

Class-prior Estimation for Learning from Positive and Unlabeled Data.
Proceedings of The 7th Asian Conference on Machine Learning, 2015

Continuous Target Shift Adaptation in Supervised Learning.
Proceedings of The 7th Asian Conference on Machine Learning, 2015

Geometry-Aware Principal Component Analysis for Symmetric Positive Definite Matrices.
Proceedings of The 7th Asian Conference on Machine Learning, 2015

Support Consistency of Direct Sparse-Change Learning in Markov Networks.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Statistical Reinforcement Learning - Modern Machine Learning Approaches.
Chapman and Hall / CRC machine learning and pattern recognition series, CRC Press, ISBN: 978-1-439-85689-5, 2015

2014
A least-squares approach to anomaly detection in static and sequential data.
Pattern Recognition Letters, 2014

Model-based policy gradients with parameter-based exploration by least-squares conditional density estimation.
Neural Networks, 2014

Semi-supervised learning of class balance under class-prior change by distribution matching.
Neural Networks, 2014

Semi-supervised information-maximization clustering.
Neural Networks, 2014

High-Dimensional Feature Selection by Feature-Wise Kernelized Lasso.
Neural Computation, 2014

Information-Maximization Clustering Based on Squared-Loss Mutual Information.
Neural Computation, 2014

Information-Theoretic Semi-Supervised Metric Learning via Entropy Regularization.
Neural Computation, 2014

Direct Learning of Sparse Changes in Markov Networks by Density Ratio Estimation.
Neural Computation, 2014

Least-squares independence regression for non-linear causal inference under non-Gaussian noise.
Machine Learning, 2014

Tree-Based Ensemble Multi-Task Learning Method for Classification and Regression.
IEICE Transactions, 2014

Computationally Efficient Estimation of Squared-Loss Mutual Information with Multiplicative Kernel Models.
IEICE Transactions, 2014

Unsupervised Dimension Reduction via Least-Squares Quadratic Mutual Information.
IEICE Transactions, 2014

Class Prior Estimation from Positive and Unlabeled Data.
IEICE Transactions, 2014

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

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

Conditional Density Estimation with Dimensionality Reduction via Squared-Loss Conditional Entropy Minimization.
CoRR, 2014

Efficient Reuse of Previous Experiences to Improve Policies in Real Environment.
CoRR, 2014

Transductive Learning with Multi-class Volume Approximation.
CoRR, 2014

Support vector comparison machines.
CoRR, 2014

Clustering via Mode Seeking by Direct Estimation of the Gradient of a Log-Density.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

An Online Policy Gradient Algorithm for Markov Decision Processes with Continuous States and Actions.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

Multitask learning meets tensor factorization: task imputation via convex optimization.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Analysis of Learning from Positive and Unlabeled Data.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Analysis of Variational Bayesian Latent Dirichlet Allocation: Weaker Sparsity Than MAP.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Outlier Path: A Homotopy Algorithm for Robust SVM.
Proceedings of the 31th International Conference on Machine Learning, 2014

Transductive Learning with Multi-class Volume Approximation.
Proceedings of the 31th International Conference on Machine Learning, 2014

Efficient reuse of previous experiences in humanoid motor learning.
Proceedings of the 14th IEEE-RAS International Conference on Humanoid Robots, 2014

Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

Analysis of Empirical MAP and Empirical Partially Bayes: Can They be Alternatives to Variational Bayes?
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013
Change-point detection in time-series data by relative density-ratio estimation.
Neural Networks, 2013

Efficient Sample Reuse in Policy Gradients with Parameter-Based Exploration.
Neural Computation, 2013

Relative Density-Ratio Estimation for Robust Distribution Comparison.
Neural Computation, 2013

Sufficient Dimension Reduction via Squared-Loss Mutual Information Estimation.
Neural Computation, 2013

Density-Difference Estimation.
Neural Computation, 2013

Variational Bayesian sparse additive matrix factorization.
Machine Learning, 2013

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

Maximum volume clustering: a new discriminative clustering approach.
Journal of Machine Learning Research, 2013

Global analytic solution of fully-observed variational Bayesian matrix factorization.
Journal of Machine Learning Research, 2013

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

Artist Agent: A Reinforcement Learning Approach to Automatic Stroke Generation in Oriental Ink Painting.
IEICE Transactions, 2013

Direct Approximation of Quadratic Mutual Information and Its Application to Dependence-Maximization Clustering.
IEICE Transactions, 2013

Computationally Efficient Multi-Label Classification by Least-Squares Probabilistic Classifiers.
IEICE Transactions, 2013

Feature Selection via l1-Penalized Squared-Loss Mutual Information.
IEICE Transactions, 2013

Winning the Kaggle Algorithmic Trading Challenge with the Composition of Many Models and Feature Engineering.
IEICE Transactions, 2013

Machine Learning with Squared-Loss Mutual Information.
Entropy, 2013

Noise adaptive optimization of matrix initialization for frequency-domain independent component analysis.
Digital Signal Processing, 2013

Clustering Unclustered Data: Unsupervised Binary Labeling of Two Datasets Having Different Class Balances
CoRR, 2013

Semi-Supervised Information-Maximization Clustering
CoRR, 2013

Density Ratio Hidden Markov Models
CoRR, 2013

Efficient Sample Reuse in Policy Gradients with Parameter-based Exploration
CoRR, 2013

Model-Based Policy Gradients with Parameter-Based Exploration by Least-Squares Conditional Density Estimation.
CoRR, 2013

Clustering Unclustered Data: Unsupervised Binary Labeling of Two Datasets Having Different Class Balances.
Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2013

Direct Learning of Sparse Changes in Markov Networks by Density Ratio Estimation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Parametric Task Learning.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Global Solver and Its Efficient Approximation for Variational Bayesian Low-rank Subspace Clustering.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Infinitesimal Annealing for Training Semi-Supervised Support Vector Machines.
Proceedings of the 30th International Conference on Machine Learning, 2013

Squared-loss Mutual Information Regularization: A Novel Information-theoretic Approach to Semi-supervised Learning.
Proceedings of the 30th International Conference on Machine Learning, 2013

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

Introduction to the Special Section on the 2nd Asia Conference on Machine Learning (ACML 2010).
ACM TIST, 2012

Sequential change-point detection based on direct density-ratio estimation.
Statistical Analysis and Data Mining, 2012

Analysis and improvement of policy gradient estimation.
Neural Networks, 2012

Improving importance estimation in pool-based batch active learning for approximate linear regression.
Neural Networks, 2012

Canonical dependency analysis based on squared-loss mutual information.
Neural Networks, 2012

Multi-parametric solution-path algorithm for instance-weighted support vector machines.
Machine Learning, 2012

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

Fast Learning Rate of Multiple Kernel Learning: Trade-Off between Sparsity and Smoothness.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Sparse Additive Matrix Factorization for Robust PCA and Its Generalization.
Proceedings of the 4th Asian Conference on Machine Learning, 2012

Importance-weighted least-squares probabilistic classifier for covariate shift adaptation with application to human activity recognition.
Neurocomputing, 2012

On Kernel Parameter Selection in Hilbert-Schmidt Independence Criterion.
IEICE Transactions, 2012

Multi-Task Approach to Reinforcement Learning for Factored-State Markov Decision Problems.
IEICE Transactions, 2012

Early Stopping Heuristics in Pool-Based Incremental Active Learning for Least-Squares Probabilistic Classifier.
IEICE Transactions, 2012

Feature Selection via L1-Penalized Squared-Loss Mutual Information
CoRR, 2012

Designing various component analysis at will
CoRR, 2012

Density-Difference Estimation
CoRR, 2012

Semi-Supervised Learning of Class Balance under Class-Prior Change by Distribution Matching
CoRR, 2012

Artist Agent: A Reinforcement Learning Approach to Automatic Stroke Generation in Oriental Ink Painting
CoRR, 2012

Information-theoretic Semi-supervised Metric Learning via Entropy Regularization
CoRR, 2012

Dependence Maximizing Temporal Alignment via Squared-Loss Mutual Information
CoRR, 2012

Parametric Return Density Estimation for Reinforcement Learning
CoRR, 2012

Change-Point Detection in Time-Series Data by Relative Density-Ratio Estimation
CoRR, 2012

High-Dimensional Feature Selection by Feature-Wise Non-Linear Lasso
CoRR, 2012

Change-Point Detection in Time-Series Data by Relative Density-Ratio Estimation.
Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 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

Perfect Dimensionality Recovery by Variational Bayesian PCA.
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

Designing various component analysis at will.
Proceedings of the 21st International Conference on Pattern Recognition, 2012

Artist Agent: A Reinforcement Learning Approach to Automatic Stroke Generation in Oriental Ink Painting.
Proceedings of the 29th International Conference on Machine Learning, 2012

Semi-Supervised Learning of Class Balance under Class-Prior Change by Distribution Matching.
Proceedings of the 29th International Conference on Machine Learning, 2012

Information-theoretic Semi-supervised Metric Learning via Entropy Regularization.
Proceedings of the 29th International Conference on Machine Learning, 2012

Computationally efficient multi-label classification by least-squares probabilistic classifier.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

Machine Learning in Non-Stationary Environments - Introduction to Covariate Shift Adaptation.
Adaptive computation and machine learning, MIT Press, ISBN: 978-0-262-01709-1, 2012

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

2011
Active Learning in Recommender Systems.
Proceedings of the Recommender Systems Handbook, 2011

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

Least-Squares Independent Component Analysis.
Neural Computation, 2011

Reward-Weighted Regression with Sample Reuse for Direct Policy Search in Reinforcement Learning.
Neural Computation, 2011

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

Cross-Domain Object Matching with Model Selection.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Suffcient Component Analysis.
Proceedings of the 3rd Asian Conference on Machine Learning, 2011

A Refined Margin Analysis for Boosting Algorithms via Equilibrium Margin.
Journal of Machine Learning Research, 2011

Super-Linear Convergence of Dual Augmented Lagrangian Algorithm for Sparsity Regularized Estimation.
Journal of Machine Learning Research, 2011

Maximum Volume Clustering.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Theoretical Analysis of Bayesian Matrix Factorization.
Journal of Machine Learning Research, 2011

Dependence-Maximization Clustering with Least-Squares Mutual Information.
JACIII, 2011

Computationally Efficient Multi-task Learning with Least-squares Probabilistic Classifiers.
IPSJ Trans. Computer Vision and Applications, 2011

Improving the Accuracy of Least-Squares Probabilistic Classifiers.
IEICE Transactions, 2011

Lighting Condition Adaptation for Perceived Age Estimation.
IEICE Transactions, 2011

Least-Squares Independence Test.
IEICE Transactions, 2011

Foreword.
IEICE Transactions, 2011

Analysis and Improvement of Policy Gradient Estimation.
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

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

Target Neighbor Consistent Feature Weighting for Nearest Neighbor Classification.
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

Global Solution of Fully-Observed Variational Bayesian Matrix Factorization is Column-Wise Independent.
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

Multi-parametric solution-path algorithm for instance-weighted support vector machines.
Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011

On Information-Maximization Clustering: Tuning Parameter Selection and Analytic Solution.
Proceedings of the 28th International Conference on Machine Learning, 2011

On Bayesian PCA: Automatic Dimensionality Selection and Analytic Solution.
Proceedings of the 28th International Conference on Machine Learning, 2011

Detection of activities and events without explicit categorization.
Proceedings of the IEEE International Conference on Computer Vision Workshops, 2011

Automatic audio tag classification via semi-supervised canonical density estimation.
Proceedings of the IEEE International Conference on Acoustics, 2011

Multi-race age estimation based on the combination of multiple classifiers.
Proceedings of the First Asian Conference on Pattern Recognition, 2011

Direct Density-Ratio Estimation with Dimensionality Reduction via Hetero-Distributional Subspace Analysis.
Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

Trajectory Regression on Road Networks.
Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010
Conic Programming for Multitask Learning.
IEEE Trans. Knowl. Data Eng., 2010

Application of Covariate Shift Adaptation Techniques in Brain-Computer Interfaces.
IEEE Trans. Biomed. Engineering, 2010

Semi-supervised speaker identification under covariate shift.
Signal Processing, 2010

Dimensionality reduction for density ratio estimation in high-dimensional spaces.
Neural Networks, 2010

Efficient exploration through active learning for value function approximation in reinforcement learning.
Neural Networks, 2010

Semi-supervised local Fisher discriminant analysis for dimensionality reduction.
Machine Learning, 2010

Single versus Multiple Sorting in All Pairs Similarity Search.
Proceedings of the 2nd Asian Conference on Machine Learning, 2010

Sufficient Dimension Reduction via Squared-loss Mutual Information Estimation.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Preface.
Proceedings of the 2nd Asian Conference on Machine Learning, 2010

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

A Transfer Learning Approach and Selective Integration of Multiple Types of Assays for Biological Network Inference.
IJKDB, 2010

Direct Importance Estimation with a Mixture of Probabilistic Principal Component Analyzers.
IEICE Transactions, 2010

A Semi-Supervised Approach to Perceived Age Prediction from Face Images.
IEICE Transactions, 2010

Least-Squares Conditional Density Estimation.
IEICE Transactions, 2010

Least Absolute Policy Iteration--A Robust Approach to Value Function Approximation.
IEICE Transactions, 2010

Superfast-Trainable Multi-Class Probabilistic Classifier by Least-Squares Posterior Fitting.
IEICE Transactions, 2010

Foreword.
IEICE Transactions, 2010

Spectral Methods for Thesaurus Construction.
IEICE Transactions, 2010

Theoretical Analysis of Density Ratio Estimation.
IEICE Transactions, 2010

Multi-parametric Solution-path Algorithm for Instance-weighted Support Vector Machines
CoRR, 2010

Semi-supervised Estimation of Perceived Age from Face Images.
Proceedings of the VISAPP 2010 - Proceedings of the Fifth International Conference on Computer Vision Theory and Applications, Angers, France, May 17-21, 2010, 2010

Parametric Return Density Estimation for Reinforcement Learning.
Proceedings of the UAI 2010, 2010

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

Feature Selection for Reinforcement Learning: Evaluating Implicit State-Reward Dependency via Conditional Mutual Information.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Global Analytic Solution for Variational Bayesian Matrix Factorization.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Perceived Age Estimation under Lighting Condition Change by Covariate Shift Adaptation.
Proceedings of the 20th International Conference on Pattern Recognition, 2010

SemiCCA: Efficient Semi-supervised Learning of Canonical Correlations.
Proceedings of the 20th International Conference on Pattern Recognition, 2010

A Fast Augmented Lagrangian Algorithm for Learning Low-Rank Matrices.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Implicit Regularization in Variational Bayesian Matrix Factorization.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Nonparametric Return Distribution Approximation for Reinforcement Learning.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Acceleration of sequence kernel computation for real-time speaker identification.
Proceedings of the IEEE International Conference on Acoustics, 2010

Direct importance estimation with probabilistic principal component analyzers.
Proceedings of the IEEE International Conference on Acoustics, 2010

Automatic audio tagging using covariate shift adaptation.
Proceedings of the IEEE International Conference on Acoustics, 2010

Dependence Minimizing Regression with Model Selection for Non-Linear Causal Inference under Non-Gaussian Noise.
Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

2009
Robust Label Propagation on Multiple Networks.
IEEE Trans. Neural Networks, 2009

Dual-Augmented Lagrangian Method for Efficient Sparse Reconstruction.
IEEE Signal Process. Lett., 2009

Adaptive importance sampling for value function approximation in off-policy reinforcement learning.
Neural Networks, 2009

On Generalization Performance and Non-Convex Optimization of Extended nu-Support Vector Machine.
New Generation Comput., 2009

Theory and Algorithm for Learning with Dissimilarity Functions.
Neural Computation, 2009

Pool-based active learning in approximate linear regression.
Machine Learning, 2009

Lanczos Approximations for the Speedup of Kernel Partial Least Squares Regression.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

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

Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation.
JIP, 2009

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

Direct Importance Estimation with Gaussian Mixture Models.
IEICE Transactions, 2009

On Computational Issues of Semi-Supervised Local Fisher Discriminant Analysis.
IEICE Transactions, 2009

Recent Advances and Trends in Large-Scale Kernel Methods.
IEICE Transactions, 2009

Efficient Construction of Neighborhood Graphs by the Multiple Sorting Method
CoRR, 2009

Super-Linear Convergence of Dual Augmented-Lagrangian Algorithm for Sparsity Regularized Estimation.
CoRR, 2009

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

Simultaneous inference of biological networks of multiple species from genome-wide data and evolutionary information: a semi-supervised approach.
Bioinformatics, 2009

Change-Point Detection in Time-Series Data by Direct Density-Ratio Estimation.
Proceedings of the SIAM International Conference on Data Mining, 2009

Link Propagation: A Fast Semi-supervised Learning Algorithm for Link Prediction.
Proceedings of the SIAM International Conference on Data Mining, 2009

Efficient Sample Reuse in EM-Based Policy Search.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

Analysis of Variational Bayesian Matrix Factorization.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2009

Mutual information approximation via maximum likelihood estimation of density ratio.
Proceedings of the IEEE International Symposium on Information Theory, 2009

Probabilistic principal component analysis based on JoyStick Probability Selector.
Proceedings of the International Joint Conference on Neural Networks, 2009

Active Policy Iteration: Efficient Exploration through Active Learning for Value Function Approximation in Reinforcement Learning.
Proceedings of the IJCAI 2009, 2009

Estimating Squared-Loss Mutual Information for Independent Component Analysis.
Proceedings of the Independent Component Analysis and Signal Separation, 2009

Least absolute policy iteration for robust value function approximation.
Proceedings of the 2009 IEEE International Conference on Robotics and Automation, 2009

Covariate shift adaptation for semi-supervised speaker identification.
Proceedings of the IEEE International Conference on Acoustics, 2009

A Framework of Adaptive Brain Computer Interfaces.
Proceedings of the 2nd International Conference on BioMedical Engineering and Informatics, 2009

Efficient data reuse in value function approximation.
Proceedings of the IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, 2009

Density Ratio Estimation: A New Versatile Tool for Machine Learning.
Proceedings of the Advances in Machine Learning, 2009

2008
A Multipurpose Linear Component Analysis Method Based on Modulated Hebb-Oja Learning Rule.
IEEE Signal Process. Lett., 2008

A batch ensemble approach to active learning with model selection.
Neural Networks, 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

Approximating the Best Linear Unbiased Estimator of Non-Gaussian Signals with Gaussian Noise.
IEICE Transactions, 2008

Geodesic Gaussian kernels for value function approximation.
Auton. Robots, 2008

Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation.
Proceedings of the SIAM International Conference on Data Mining, 2008

Active Learning with Model Selection in Linear Regression.
Proceedings of the SIAM International Conference on Data Mining, 2008

Integration of Multiple Networks for Robust Label Propagation.
Proceedings of the SIAM International Conference on Data Mining, 2008

Pool-Based Agnostic Experiment Design in Linear Regression.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2008

Semi-Supervised Local Fisher Discriminant Analysis for Dimensionality Reduction.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2008

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

Order Retrieval.
Proceedings of the Large-Scale Knowledge Resources. Construction and Application, 2008

nu-support vector machine as conditional value-at-risk minimization.
Proceedings of the Machine Learning, 2008

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

On the Margin Explanation of Boosting Algorithms.
Proceedings of the 21st Annual Conference on Learning Theory, 2008

Adaptive Importance Sampling with Automatic Model Selection in Value Function Approximation.
Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007
Covariate Shift Adaptation by Importance Weighted Cross Validation.
Journal of Machine Learning Research, 2007

Dimensionality Reduction of Multimodal Labeled Data by Local Fisher Discriminant Analysis.
Journal of Machine Learning Research, 2007

Generalization Error Estimation for Non-linear Learning Methods.
IEICE Transactions, 2007

A New Meta-Criterion for Regularized Subspace Information Criterion.
IEICE Transactions, 2007

Analytic Optimization of Adaptive Ridge Parameters Based on Regularized Subspace Information Criterion.
IEICE Transactions, 2007

Influence-based collaborative active learning.
Proceedings of the 2007 ACM Conference on Recommender Systems, 2007

Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Multi-Task Learning via Conic Programming.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Value Function Approximation on Non-Linear Manifolds for Robot Motor Control.
Proceedings of the 2007 IEEE International Conference on Robotics and Automation, 2007

Asymptotic Bayesian generalization error when training and test distributions are different.
Proceedings of the Machine Learning, 2007

2006
Active Learning in Approximately Linear Regression Based on Conditional Expectation of Generalization Error.
Journal of Machine Learning Research, 2006

In Search of Non-Gaussian Components of a High-Dimensional Distribution.
Journal of Machine Learning Research, 2006

Analytic Optimization of Shrinkage Parameters Based on Regularized Subspace Information Criterion.
IEICE Transactions, 2006

Constructing Kernel Functions for Binary Regression.
IEICE Transactions, 2006

Model Selection Using a Class of Kernels with an Invariant Metric.
Proceedings of the Structural, 2006

Mixture Regression for Covariate Shift.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Local Fisher discriminant analysis for supervised dimensionality reduction.
Proceedings of the Machine Learning, 2006

Obtaining the Best Linear Unbiased Estimator of Noisy Signals by Non-Gaussian Component Analysis.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

A Novel Dimension Reduction Procedure for Searching Non-Gaussian Subspaces.
Proceedings of the Independent Component Analysis and Blind Signal Separation, 2006

Importance-Weighted Cross-Validation for Covariate Shift.
Proceedings of the Pattern Recognition, 2006

2005
Active Learning for Misspecified Models.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Non-Gaussian Component Analysis: a Semi-parametric Framework for Linear Dimension Reduction.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Model Selection Under Covariate Shift.
Proceedings of the Artificial Neural Networks: Formal Models and Their Applications, 2005

2004
Trading Variance Reduction with Unbiasedness: The Regularized Subspace Information Criterion for Robust Model Selection in Kernel Regression.
Neural Computation, 2004

Estimating the error at given test input points for linear regression.
Proceedings of the IASTED International Conference on Neural Networks and Computational Intelligence, 2004

Regularizing generalization error estimators: a novel approach to robust model selection.
Proceedings of the ESANN 2004, 2004

2002
Subspace information criterion for nonquadratic regularizers-Model selection for sparse regressors.
IEEE Trans. Neural Networks, 2002

A unified method for optimizing linear image restoration filters.
Signal Processing, 2002

Optimal design of regularization term and regularization parameter by subspace information criterion.
Neural Networks, 2002

Theoretical and Experimental Evaluation of the Subspace Information Criterion.
Machine Learning, 2002

The Subspace Information Criterion for Infinite Dimensional Hypothesis Spaces.
Journal of Machine Learning Research, 2002

Selecting Ridge Parameters in Infinite Dimensional Hypothesis Spaces.
Proceedings of the Artificial Neural Networks, 2002

2001
Properties of incremental projection learning.
Neural Networks, 2001

Incremental projection learning for optimal generalization.
Neural Networks, 2001

Incremental Active Learning for Optimal Generalization.
Neural Computation, 2001

Subspace Information Criterion for Model Selection.
Neural Computation, 2001

2000
Incremental Active Learning with Bias Reduction.
IJCNN (1), 2000

A new information criterion for the selection of subspace models.
Proceedings of the ESANN 2000, 2000

1999
Training Data Selection for Optimal Generalization in Trigonometric Polynomial Networks.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999


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