Learning Graphical Models
A graphical model or probabilistic graphical model (PGM) or structured probabilistic model is a probabilistic model for which a graph expresses the conditional dependence structure between random variables. They are commonly used in probability theory, statistics—particularly Bayesian statistics—and machine learning. (Wikipedia)
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Efficient Model-Free Exploration in Low-Rank MDPs
Neural Information Processing Systems
What are the right computational primitives for exploration?
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ODE-based Recurrent Model-free Reinforcement Learning for POMDPs
Neural Information Processing Systems
In partially observable (PO) environments, how to infer unseen information from raw observations puzzled the agents.
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