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Transferred Q-learning
We consider $Q$-learning with knowledge transfer, using samples from a target reinforcement learning (RL) task as well as source samples from different but related RL tasks.
Reinforcement Learning with Heterogeneous Data: Estimation and Inference
Reinforcement Learning (RL) has the promise of providing data-driven support for decision-making in a wide range of problems in healthcare, education, business, and other domains.
On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification
Yet, the behavior of minimum Wasserstein estimators is poorly understood, notably in high-dimensional regimes or under model misspecification.
Low-Rank Principal Eigenmatrix Analysis
Sparse PCA is a widely used technique for high-dimensional data analysis.
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