Sugiyama Masashi | Tokyo Inst. Of Technol. Tokyo Jpn

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概要

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著作論文

Statistical active learning for efficient value function approximation in reinforcement learning (ニューロコンピューティング)
Improving the Accuracy of Least-Squares Probabilistic Classifiers
Improving the Accuracy of Least-Squares Probabilistic Classifiers
A New Meta-Criterion for Regularized Subspace Information Criterion
Approximating the Best Linear Unbiased Estimator of Non-Gaussian Signals with Gaussian Noise
A new algorithm of non-Gaussian component analysis with radial kernel functions (Special issue: Information geometry and its applications)
Multi-task learning with least-squares probabilistic classifiers (パターン認識・メディア理解)
Multi-task learning with least-squares probabilistic classifiers (情報論的学習理論と機械学習)
Adaptive importance sampling with automatic model selection in value function approximation (ニューロコンピューティング)
Analytic Optimization of Adaptive Ridge Parameters Based on Regularized Subspace Information Criterion(Neural Networks and Bioengineering)
Adaptive Ridge Learning in Kernel Eigenspace and Its Model Selection
Improving Model-based Reinforcement Learning with Multitask Learning
Improving Model-based Reinforcement Learning with Multitask Learning
Improving Importance Estimation in Pool-based Batch Active Learning for Approximate Linear Regression (情報論的学習理論と機械学習)
Early Stopping Heuristics in Pool-Based Incremental Active Learning for Least-Squares Probabilistic Classifier (情報論的学習理論と機械学習)

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