Hachiya Hirotaka | Tokyo Inst. Of Technol.

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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)
Adaptive importance sampling with automatic model selection in value function approximation (ニューロコンピューティング)
Improving Model-based Reinforcement Learning with Multitask Learning
Improving Model-based Reinforcement Learning with Multitask Learning
Least-Squares Conditional Density Estimation
Information-maximization clustering: analytic solution and model selection (情報論的学習理論と機械学習)
Conditional Density Estimation Based on Density Ratio Estimation
Conditional Density Estimation Based on Density Ratio Estimation
Least Absolute Policy Iteration-A Robust Approach to Value Function Approximation
Analysis and improvement of policy gradient estimation (情報論的学習理論と機械学習)
Artist agent A[2]: stroke painterly rendering based on reinforcement learning (パターン認識・メディア理解)
Artist agent A[2]: stroke painterly rendering based on reinforcement learning (情報論的学習理論と機械学習)
Efficient Sample Reuse in Policy Gradients with Parameter-based Exploration (情報論的学習理論と機械学習)
Modified Newton Approach to Policy Search (情報論的学習理論と機械学習)
Relative Density-Ratio Estimation for Robust Distribution Comparison (情報論的学習理論と機械学習)
Artist Agent: A Reinforcement Learning Approach to Automatic Stroke Generation in Oriental Ink Painting
Computationally Efficient Multi-Label Classification by Least-Squares Probabilistic Classifiers
Multi-Task Approach to Reinforcement Learning for Factored-State Markov Decision Problems
Efficient Sample Reuse in Policy Gradients with Parameter-based Exploration (情報論的学習理論と機械学習)

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