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Department Of Computer Science Tokyo Institute Of Technology | 論文
- New feature selection method for reinforcement learning: conditional mutual information reveals implicit state-reward dependency (情報論的学習理論と機械学習)
- Least Absolute Policy Iteration-A Robust Approach to Value Function Approximation
- Independent component analysis by direct density-ratio estimation (ニューロコンピューティング)
- A New Meta-Criterion for Regularized Subspace Information Criterion(Pattern Recognition)
- Spectral Methods for Thesaurus Construction
- Adaptive importance sampling with automatic model selection in reward weighted regression (ニューロコンピューティング)
- Preprocessing Planning for Data Mining(Artificial Intelligence I)
- Preprocessing Planning for Data Mining(Artificial Intelligence I)(Joint Workshop of Vietnamese Society of AI, SIGKBS-JSAI, ICS-IPSJ, and IEICE-SIGAI on Active Mining)
- Partial Order Reduction in Symbolic State Space Traversal Using ZBDDs
- α-Methoxy-α-trifluoromethylpropionic Acid (MTPr). A New Chiral Derivatizing Reagent for GC Separation of Enantiomeric Amino Acids
- Some Lower Bounds of Cyclic Shift on Boolean Circuits (Special Section on Discrete Mathematics and Its Applications)
- Treatment of Big Values in an Applicative Language HFP : Translation from By-Value Access to By-Update Access
- SERAPH: semi-supervised metric learning paradigm with hyper sparsity (情報論的学習理論と機械学習)
- Manpower Scheduling with Shift Change Constraints
- On Defining Denotational Semantics for Attribute Grammars
- Verification of an Environment Management based on Operational Semantics for Static Scope Rules
- Analysis and improvement of policy gradient estimation (情報論的学習理論と機械学習)
- Direct density-ratio estimation with dimensionality reduction via hetero-distributional subspace analysis (情報論的学習理論と機械学習)
- 1. Estimate Response-based Active Learning
- Recommending collaborative activities in informal learning using Bayesian methodology