lihong li thesis

combinatorial action space for predicting and tracking popular discussion threads. Li : The online discovery problem and its application to lifelong reinforcement learning. In the 29th Conference on Uncertainty in Artificial Intelligence (UAI), 2013. On the sample complexity of reinforcement learning. L., Mesterharm,., Littman,. Wong: Composite task-completion contoh thesis student uitm dialogue system via hierarchical deep reinforcement learning.

A unifying framework for computational reinforcement
A unifying framework for computational reinforcement learning theory
Publications - Lihong Li - Research - Rutgers University
Focus of Attention in Reinforcement Learning - CiteSeerX

lihong li thesis

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Chang: Refining recency search results with user click feedback. In the 34th International Conference on Machine Learning (icml), 2017. The adaptive k -meteorologists problem and its application to structure discovery and feature selection in reinforcement learning. In this dissertation, we introduce a novel computational learning model called kwik (Knows What It Knows) that is designed particularly for its utility in analyzing learning problems like RL where active exploration can impact the training data the learner is exposed. (for general academic work) (for Google related work) 747 Sixth Street South, Kirkland, WA, USA 98033. Machine Learning, 16, 227. In Statistical Science, 29(4 485-511, 2014.

Lihong li thesis
lihong li thesis

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