
Universal OffPolicy Evaluation
When faced with sequential decisionmaking problems, it is often useful ...
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HighConfidence OffPolicy (or Counterfactual) Variance Estimation
Many sequential decisionmaking systems leverage data collected using pr...
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Towards Safe Policy Improvement for NonStationary MDPs
Many realworld sequential decisionmaking problems involve critical sys...
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Reinforcement Learning for Strategic Recommendations
Strategic recommendations (SR) refer to the problem where an intelligent...
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Evaluating the Performance of Reinforcement Learning Algorithms
Performance evaluations are critical for quantifying algorithmic advance...
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Optimizing for the Future in NonStationary MDPs
Most reinforcement learning methods are based upon the key assumption th...
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Classical Policy Gradient: Preserving Bellman's Principle of Optimality
We propose a new objective function for finitehorizon episodic Markov d...
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Reinforcement Learning When All Actions are Not Always Available
The Markov decision process (MDP) formulation used to model many realwo...
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Lifelong Learning with a Changing Action Set
In many realworld sequential decision making problems, the number of av...
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Learning Action Representations for Reinforcement Learning
Most modelfree reinforcement learning methods leverage state representa...
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Fusion Graph Convolutional Networks
Semisupervised node classification involves learning to classify unlabe...
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HOPF: Higher Order Propagation Framework for Deep Collective Classification
Given a graph wherein every node has certain attributes associated with ...
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Yash Chandak
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