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Found 7 papers, 1 papers with code
Reinforcement learning in large, structured action spaces: A simulation study of decision support for spinal cord injury rehabilitation
Reinforcement learning (RL) has helped improve decision-making in several applications.
Hybrid Feature- and Similarity-Based Models for Joint Prediction and Interpretation
Electronic health records (EHRs) include simple features like patient age together with more complex data like care history that are informative but not easily represented as individual features.
Decision-Directed Data Decomposition
We present an algorithm, Decision-Directed Data Decomposition (D4), which decomposes a dataset into two components.
On Prediction and Tolerance Intervals for Dynamic Treatment Regimes
We develop and evaluate tolerance interval methods for dynamic treatment regimes (DTRs) that can provide more detailed prognostic information to patients who will follow an estimated optimal regime.
gLOP: the global and Local Penalty for Capturing Predictive Heterogeneity
However, in practice, problems can exhibit predictive heterogeneity: most instances might be relatively easy to predict, while others might be predictive outliers for which a model trained on the entire dataset does not perform well.
Generative Multiple-Instance Learning Models For Quantitative Electromyography
We present a comprehensive study of the use of generative modeling approaches for Multiple-Instance Learning (MIL) problems.
Convergent Fitted Value Iteration with Linear Function Approximation
Fitted value iteration (FVI) with ordinary least squares regression is known to diverge.
