Masashi Sugiyama
Orcid: 0000-0001-6658-6743
According to our database1,
Masashi Sugiyama
authored at least 552 papers
between 1999 and 2024.
Collaborative distances:
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Bibliography
2024
IEEE Trans. Pattern Anal. Mach. Intell., May, 2024
Generating Chain-of-Thoughts with a Direct Pairwise-Comparison Approach to Searching for the Most Promising Intermediate Thought.
CoRR, 2024
Reinforcement Learning from Bagged Reward: A Transformer-based Approach for Instance-Level Reward Redistribution.
CoRR, 2024
Appearance-Based Curriculum for Semi-Supervised Learning with Multi-Angle Unlabeled Data.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024
Proceedings of the 12th International Winter Conference on Brain-Computer Interface, 2024
Thompson Sampling for Real-Valued Combinatorial Pure Exploration of Multi-Armed Bandit.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
The Choice of Noninformative Priors for Thompson Sampling in Multiparameter Bandit Models.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
Neural Comput., October, 2023
IEEE Trans. Pattern Anal. Mach. Intell., March, 2023
Positive-unlabeled classification under class-prior shift: a prior-invariant approach based on density ratio estimation.
Mach. Learn., March, 2023
Root cause estimation of faults in production processes: a novel approach inspired by approximate Bayesian computation.
Int. J. Prod. Res., March, 2023
Representation learning for continuous action spaces is beneficial for efficient policy learning.
Neural Networks, February, 2023
Learning with Complementary Labels Revisited: A Consistent Approach via Negative-Unlabeled Learning.
CoRR, 2023
CoRR, 2023
Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation.
CoRR, 2023
CoRR, 2023
CoRR, 2023
CoRR, 2023
Combinatorial Pure Exploration of Multi-Armed Bandit with a Real Number Action Class.
CoRR, 2023
Making Binary Classification from Multiple Unlabeled Datasets Almost Free of Supervision.
CoRR, 2023
CoRR, 2023
Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations.
CoRR, 2023
Analysis of Pleasantness Evoked by Various Airborne Ultrasound Tactile Stimuli Using Pairwise Comparisons and the Bradley-Terry Model.
CoRR, 2023
Enhancing Label Sharing Efficiency in Complementary-Label Learning with Label Augmentation.
CoRR, 2023
Assessing Vulnerabilities of Adversarial Learning Algorithm through Poisoning Attacks.
CoRR, 2023
Asymptotically Optimal Thompson Sampling Based Policy for the Uniform Bandits and the Gaussian Bandits.
CoRR, 2023
CoRR, 2023
Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Generalizing Importance Weighting to A Universal Solver for Distribution Shift Problems.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Is the Performance of My Deep Network Too Good to Be True? A Direct Approach to Estimating the Bayes Error in Binary Classification.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
Proceedings of the IEEE International Conference on Acoustics, 2023
2022
Trans. Mach. Learn. Res., 2022
IEEE Trans. Pattern Anal. Mach. Intell., 2022
Centroid Estimation With Guaranteed Efficiency: A General Framework for Weakly Supervised Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2022
Discovering diverse solutions in deep reinforcement learning by maximizing state-action-based mutual information.
Neural Networks, 2022
Neural Networks, 2022
J. Mach. Learn. Res., 2022
J. Mach. Learn. Res., 2022
IEICE Trans. Inf. Syst., 2022
Expert Syst. Appl., 2022
Equivariant Disentangled Transformation for Domain Generalization under Combination Shift.
CoRR, 2022
CoRR, 2022
Excess risk analysis for epistemic uncertainty with application to variational inference.
CoRR, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Generalizing Consistent Multi-Class Classification with Rejection to be Compatible with Arbitrary Losses.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Adversarial Training with Complementary Labels: On the Benefit of Gradually Informative Attacks.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Instance-Dependent Label-Noise Learning with Manifold-Regularized Transition Matrix Estimation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
Multi-class Classification from Multiple Unlabeled Datasets with Partial Risk Regularization.
Proceedings of the Asian Conference on Machine Learning, 2022
Proceedings of the Asian Conference on Machine Learning, 2022
2021
Direction Matters: On Influence-Preserving Graph Summarization and Max-Cut Principle for Directed Graphs.
Neural Comput., 2021
Artificial Neural Variability for Deep Learning: On Overfitting, Noise Memorization, and Catastrophic Forgetting.
Neural Comput., 2021
Neural Comput., 2021
Classification From Pairwise Similarities/Dissimilarities and Unlabeled Data via Empirical Risk Minimization.
Neural Comput., 2021
Neural Comput., 2021
Seeing Differently, Acting Similarly: Imitation Learning with Heterogeneous Observations.
CoRR, 2021
Source-free Domain Adaptation via Distributional Alignment by Matching Batch Normalization Statistics.
CoRR, 2021
Autom., 2021
Incorporating causal graphical prior knowledge into predictive modeling via simple data augmentation.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Loss function based second-order Jensen inequality and its application to particle variational inference.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Learning Noise Transition Matrix from Only Noisy Labels via Total Variation Regularization.
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection.
Proceedings of the 38th International Conference on Machine Learning, 2021
Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences.
Proceedings of the 38th International Conference on Machine Learning, 2021
Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization.
Proceedings of the 38th International Conference on Machine Learning, 2021
Binary Classification from Multiple Unlabeled Datasets via Surrogate Set Classification.
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
A Diffusion Theory For Deep Learning Dynamics: Stochastic Gradient Descent Exponentially Favors Flat Minima.
Proceedings of the 9th International Conference on Learning Representations, 2021
Scalable Evaluation and Improvement of Document Set Expansion via Neural Positive-Unlabeled Learning.
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021
Proceedings of the CIKM 2021 Workshops co-located with 30th ACM International Conference on Information and Knowledge Management (CIKM 2021), 2021
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
γ-ABC: Outlier-Robust Approximate Bayesian Computation Based on a Robust Divergence Estimator.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
Fenchel-Young Losses with Skewed Entropies for Class-posterior Probability Estimation.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
2020
Neural Comput., 2020
Polynomial-Time Algorithms for Multiple-Arm Identification with Full-Bandit Feedback.
Neural Comput., 2020
Principled analytic classifier for positive-unlabeled learning via weighted integral probability metric.
Mach. Learn., 2020
Unsupervised key frame selection using information theory and colour histogram difference.
Int. J. Bus. Intell. Data Min., 2020
Combinatorial Pure Exploration with Full-bandit Feedback and Beyond: Solving Combinatorial Optimization under Uncertainty with Limited Observation.
CoRR, 2020
CoRR, 2020
CoRR, 2020
CoRR, 2020
LFD-ProtoNet: Prototypical Network Based on Local Fisher Discriminant Analysis for Few-shot Learning.
CoRR, 2020
Similarity-based Classification: Connecting Similarity Learning to Binary Classification.
CoRR, 2020
CoRR, 2020
CoRR, 2020
A Diffusion Theory for Deep Learning Dynamics: Stochastic Gradient Descent Escapes From Sharp Minima Exponentially Fast.
CoRR, 2020
Partially Zero-shot Domain Adaptation from Incomplete Target Data with Missing Classes.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Coupling-based Invertible Neural Networks Are Universal Diffeomorphism Approximators.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Normalized Flat Minima: Exploring Scale Invariant Definition of Flat Minima for Neural Networks Using PAC-Bayesian Analysis.
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Unbiased Risk Estimators Can Mislead: A Case Study of Learning with Complementary Labels.
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the Conference on Learning Theory, 2020
Mitigating Overfitting in Supervised Classification from Two Unlabeled Datasets: A Consistent Risk Correction Approach.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
Calibrated Surrogate Maximization of Linear-fractional Utility in Binary Classification.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
2019
Proceedings of the Explainable AI: Interpreting, 2019
IEEE Trans. Biomed. Eng., 2019
Foreword: special issue for the journal track of the 10th Asian Conference on Machine Learning (ACML 2018).
Mach. Learn., 2019
A unified view of likelihood ratio and reparameterization gradients and an optimal importance sampling scheme.
CoRR, 2019
Reducing Overestimation Bias in Multi-Agent Domains Using Double Centralized Critics.
CoRR, 2019
Pilot Study on Verifying the Monotonic Relationship between Error and Uncertainty in Deformable Registration for Neurosurgery.
CoRR, 2019
Solving NP-Hard Problems on Graphs by Reinforcement Learning without Domain Knowledge.
CoRR, 2019
CoRR, 2019
Polynomial-time Algorithms for Combinatorial Pure Exploration with Full-bandit Feedback.
CoRR, 2019
CoRR, 2019
CoRR, 2019
CoRR, 2019
Revisiting Sample Selection Approach to Positive-Unlabeled Learning: Turning Unlabeled Data into Positive rather than Negative.
CoRR, 2019
An analytic formulation for positive-unlabeled learning via weighted integral probability metric.
CoRR, 2019
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of the 7th International Conference on Learning Representations, 2019
On the Minimal Supervision for Training Any Binary Classifier from Only Unlabeled Data.
Proceedings of the 7th International Conference on Learning Representations, 2019
Proceedings of the IEEE International Conference on Acoustics, 2019
Binary Classification Only from Unlabeled Data by Iterative Unlabeled-unlabeled Classification.
Proceedings of the IEEE International Conference on Acoustics, 2019
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019
Proceedings of The 11th Asian Conference on Machine Learning, 2019
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019
Bézier Simplex Fitting: Describing Pareto Fronts of Simplicial Problems with Small Samples in Multi-Objective Optimization.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019
2018
Neural Networks, 2018
Sufficient Dimension Reduction via Direct Estimation of the Gradients of Logarithmic Conditional Densities.
Neural Comput., 2018
Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence.
Neural Comput., 2018
Correction to: Semi-supervised AUC optimization based on positive-unlabeled learning.
Mach. Learn., 2018
Mach. Learn., 2018
IEICE Trans. Inf. Syst., 2018
Pumpout: A Meta Approach for Robustly Training Deep Neural Networks with Noisy Labels.
CoRR, 2018
Alternate Estimation of a Classifier and the Class-Prior from Positive and Unlabeled Data.
CoRR, 2018
Matrix Co-completion for Multi-label Classification with Missing Features and Labels.
CoRR, 2018
Using the variogram for vector outlier screening: application to feature-based image registration.
Int. J. Comput. Assist. Radiol. Surg., 2018
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018
Analysis of Minimax Error Rate for Crowdsourcing and Its Application to Worker Clustering Model.
Proceedings of the 35th International Conference on Machine Learning, 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
Proceedings of the 6th International Conference on Learning Representations, 2018
Proceedings of the 6th International Conference on Learning Representations, 2018
Multi Task Learning with Positive and Unlabeled Data and its Application to Mental State Prediction.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018
2017
Direct Estimation of the Derivative of Quadratic Mutual Information with Application in Supervised Dimension Reduction.
Neural Comput., 2017
Mach. Learn., 2017
Mach. Learn., 2017
Geometry-aware principal component analysis for symmetric positive definite matrices.
Mach. Learn., 2017
Foreword: special issue for the journal track of the 8th Asian conference on machine learning (ACML 2016).
Mach. Learn., 2017
Mode-Seeking Clustering and Density Ridge Estimation via Direct Estimation of Density-Derivative-Ratios.
J. Mach. Learn. Res., 2017
Tensor Networks for Dimensionality Reduction and Large-scale Optimization: Part 2 Applications and Future Perspectives.
Found. Trends Mach. Learn., 2017
CoRR, 2017
Tensor Networks for Dimensionality Reduction and Large-Scale Optimizations. Part 2 Applications and Future Perspectives.
CoRR, 2017
Risk Minimization Framework for Multiple Instance Learning from Positive and Unlabeled Bags.
CoRR, 2017
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 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
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017
Proceedings of The 9th Asian Conference on Machine Learning, 2017
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 Robotics Autom. Mag., 2016
Neural Comput., 2016
Neural Comput., 2016
An Online Policy Gradient Algorithm for Markov Decision Processes with Continuous States and Actions.
Neural Comput., 2016
Computationally Efficient Class-Prior Estimation under Class Balance Change Using Energy Distance.
IEICE Trans. Inf. Syst., 2016
Beyond the Low-density Separation Principle: A Novel Approach to Semi-supervised Learning.
CoRR, 2016
Theoretical Comparisons of Learning from Positive-Negative, Positive-Unlabeled, and Negative-Unlabeled Data.
CoRR, 2016
CoRR, 2016
Dependence maximization localization: a novel approach to 2D street-map-based robot localization.
Adv. 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
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
Proceedings of the Neural Information Processing - 23rd International Conference, 2016
Proceedings of the 33nd International Conference on Machine Learning, 2016
Proceedings of the IEEE International Conference on Automation Science and Engineering, 2016
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016
Proceedings of The 8th Asian Conference on Machine Learning, 2016
Proceedings of The 8th Asian Conference on Machine Learning, 2016
2015
Proceedings of the Recommender Systems Handbook, 2015
Pattern Recognit. Lett., 2015
IEEE Trans. Pattern Anal. Mach. Intell., 2015
Conditional Density Estimation with Dimensionality Reduction via Squared-Loss Conditional Entropy Minimization.
Neural Comput., 2015
Neural Comput., 2015
Mach. Learn., 2015
J. Mach. Learn. Res., 2015
Direct Density Ratio Estimation with Convolutional Neural Networks with Application in Outlier Detection.
IEICE Trans. Inf. Syst., 2015
CoRR, 2015
Convergence of Proximal-Gradient Stochastic Variational Inference under Non-Decreasing Step-Size Sequence.
CoRR, 2015
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
Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015
Proceedings of the 32nd International Conference on Machine Learning, 2015
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
Proceedings of The 7th Asian Conference on Machine Learning, 2015
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
Pattern Recognit. Lett., 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
Neural Comput., 2014
Neural Comput., 2014
Neural Comput., 2014
Neural Comput., 2014
Least-squares independence regression for non-linear causal inference under non-Gaussian noise.
Mach. Learn., 2014
IEICE Trans. Inf. Syst., 2014
Computationally Efficient Estimation of Squared-Loss Mutual Information with Multiplicative Kernel Models.
IEICE Trans. Inf. Syst., 2014
IEICE Trans. Inf. Syst., 2014
IEICE Trans. Inf. Syst., 2014
IEICE Trans. Inf. Syst., 2014
Statistical Analysis of Distance Estimators with Density Differences and Density Ratios.
Entropy, 2014
CoRR, 2014
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
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
Proceedings of the 31th International Conference on Machine Learning, 2014
Proceedings of the 31th International Conference on Machine Learning, 2014
Proceedings of the 14th IEEE-RAS International Conference on Humanoid Robots, 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
Neural Networks, 2013
Neural Comput., 2013
Neural Comput., 2013
Computational complexity of kernel-based density-ratio estimation: a condition number analysis.
Mach. Learn., 2013
J. Mach. Learn. Res., 2013
Global analytic solution of fully-observed variational Bayesian matrix factorization.
J. Mach. Learn. Res., 2013
Direct Divergence Approximation between Probability Distributions and Its Applications in Machine Learning.
J. Comput. Sci. Eng., 2013
Artist Agent: A Reinforcement Learning Approach to Automatic Stroke Generation in Oriental Ink Painting.
IEICE Trans. Inf. Syst., 2013
Direct Approximation of Quadratic Mutual Information and Its Application to Dependence-Maximization Clustering.
IEICE Trans. Inf. Syst., 2013
Computationally Efficient Multi-Label Classification by Least-Squares Probabilistic Classifiers.
IEICE Trans. Inf. Syst., 2013
IEICE Trans. Inf. Syst., 2013
Winning the Kaggle Algorithmic Trading Challenge with the Composition of Many Models and Feature Engineering.
IEICE Trans. Inf. Syst., 2013
Noise adaptive optimization of matrix initialization for frequency-domain independent component analysis.
Digit. Signal Process., 2013
Clustering Unclustered Data: Unsupervised Binary Labeling of Two Datasets Having Different Class Balances
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
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013
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
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
Proceedings of the Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik, 2013
Proceedings of the International Winter Workshop on Brain-Computer Interface, 2013
2012
f-Divergence Estimation and Two-Sample Homogeneity Test Under Semiparametric Density-Ratio Models.
IEEE Trans. Inf. Theory, 2012
Introduction to the Special Section on the 2nd Asia Conference on Machine Learning (ACML 2010).
ACM Trans. Intell. Syst. Technol., 2012
Stat. Anal. Data Min., 2012
Improving importance estimation in pool-based batch active learning for approximate linear regression.
Neural Networks, 2012
Neural Networks, 2012
Multi-parametric solution-path algorithm for instance-weighted support vector machines.
Mach. Learn., 2012
Mach. Learn., 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
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
IEICE Trans. Inf. Syst., 2012
Multi-Task Approach to Reinforcement Learning for Factored-State Markov Decision Problems.
IEICE Trans. Inf. Syst., 2012
Early Stopping Heuristics in Pool-Based Incremental Active Learning for Least-Squares Probabilistic Classifier.
IEICE Trans. Inf. Syst., 2012
CoRR, 2012
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
Proceedings of the 21st International Conference on Pattern Recognition, 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
Cambridge University Press, ISBN: 978-0-521-19017-6, 2012
2011
Proceedings of the Recommender Systems Handbook, 2011
Direct density-ratio estimation with dimensionality reduction via least-squares hetero-distributional subspace search.
Neural Networks, 2011
Reward-Weighted Regression with Sample Reuse for Direct Policy Search in Reinforcement Learning.
Neural Comput., 2011
Knowl. Inf. Syst., 2011
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011
Proceedings of the 3rd Asian Conference on Machine Learning, 2011
J. Mach. Learn. Res., 2011
Super-Linear Convergence of Dual Augmented Lagrangian Algorithm for Sparsity Regularized Estimation.
J. Mach. Learn. Res., 2011
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011
J. Adv. Comput. Intell. Intell. Informatics, 2011
Computationally Efficient Multi-task Learning with Least-squares Probabilistic Classifiers.
IPSJ Trans. Comput. Vis. Appl., 2011
IEICE Trans. Inf. Syst., 2011
IEICE Trans. Inf. Syst., 2011
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
On Information-Maximization Clustering: Tuning Parameter Selection and Analytic Solution.
Proceedings of the 28th International Conference on Machine Learning, 2011
Proceedings of the 28th International Conference on Machine Learning, 2011
Proceedings of the IEEE International Conference on Computer Vision Workshops, 2011
Proceedings of the IEEE International Conference on Acoustics, 2011
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
Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011
2010
IEEE Trans. Biomed. Eng., 2010
Neural Networks, 2010
Efficient exploration through active learning for value function approximation in reinforcement learning.
Neural Networks, 2010
Mach. Learn., 2010
Proceedings of the 2nd Asian Conference on Machine Learning, 2010
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010
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.
Int. J. Knowl. Discov. Bioinform., 2010
Direct Importance Estimation with a Mixture of Probabilistic Principal Component Analyzers.
IEICE Trans. Inf. Syst., 2010
IEICE Trans. Inf. Syst., 2010
IEICE Trans. Inf. Syst., 2010
Superfast-Trainable Multi-Class Probabilistic Classifier by Least-Squares Posterior Fitting.
IEICE Trans. Inf. Syst., 2010
IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 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
Proceedings of the UAI 2010, 2010
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
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
Proceedings of the 20th International Conference on Pattern Recognition, 2010
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010
Proceedings of the IEEE International Conference on Acoustics, 2010
Proceedings of the IEEE International Conference on Acoustics, 2010
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
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 <i>nu</i>-Support Vector Machine.
New Gener. Comput., 2009
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009
J. Inf. Process., 2009
IPSJ Trans. Comput. Vis. Appl., 2009
IEICE Trans. Inf. Syst., 2009
IEICE Trans. Inf. Syst., 2009
IEICE Trans. Inf. Syst., 2009
CoRR, 2009
Mutual information estimation reveals global associations between stimuli and biological processes.
BMC Bioinform., 2009
Simultaneous inference of biological networks of multiple species from genome-wide data and evolutionary information: a semi-supervised approach.
Bioinform., 2009
Proceedings of the SIAM International Conference on Data Mining, 2009
Proceedings of the SIAM International Conference on Data Mining, 2009
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2009
Proceedings of the IEEE International Symposium on Information Theory, 2009
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
Proceedings of the Independent Component Analysis and Signal Separation, 2009
Proceedings of the 2009 IEEE International Conference on Robotics and Automation, 2009
Proceedings of the IEEE International Conference on Acoustics, 2009
Proceedings of the 2nd International Conference on BioMedical Engineering and Informatics, 2009
Proceedings of the IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, 2009
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
Neural Networks, 2008
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 Trans. Inf. Syst., 2008
Proceedings of the SIAM International Conference on Data Mining, 2008
Proceedings of the SIAM International Conference on Data Mining, 2008
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2008
Efficient Direct Density Ratio Estimation for Non-stationarity Adaptation and Outlier Detection.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008
Proceedings of the Large-Scale Knowledge Resources. Construction and Application, 2008
Proceedings of the Machine Learning, 2008
Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008
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
J. Mach. Learn. Res., 2007
Dimensionality Reduction of Multimodal Labeled Data by Local Fisher Discriminant Analysis.
J. Mach. Learn. Res., 2007
IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2007
IEICE Trans. Inf. Syst., 2007
Analytic Optimization of Adaptive Ridge Parameters Based on Regularized Subspace Information Criterion.
IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2007
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
Proceedings of the Advances in Neural Information Processing Systems 20, 2007
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.
J. Mach. Learn. Res., 2006
J. Mach. Learn. Res., 2006
Analytic Optimization of Shrinkage Parameters Based on Regularized Subspace Information Criterion.
IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2006
Proceedings of the Structural, 2006
Proceedings of the Advances in Neural Information Processing Systems 19, 2006
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
Proceedings of the Independent Component Analysis and Blind Signal Separation, 2006
Proceedings of the Pattern Recognition, 2006
2005
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
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 Comput., 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 12th European Symposium on Artificial Neural Networks, 2004
2003
IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2003
2002
Subspace information criterion for nonquadratic regularizers-Model selection for sparse regressors.
IEEE Trans. Neural Networks, 2002
Signal Process., 2002
Optimal design of regularization term and regularization parameter by subspace information criterion.
Neural Networks, 2002
Mach. Learn., 2002
J. Mach. Learn. Res., 2002
Proceedings of the Artificial Neural Networks, 2002
2001
2000
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000
Proceedings of the 8th European Symposium on Artificial Neural Networks, 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