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IMPROVING SENSOR NETWORK PREDICTIONS THROUGH THE IDENTIFICATION OF GRAPHICAL FEATURES
We propose a framework that represents sensor network data as a graph, extracts graphical features, and applies feature selection methods to identify the most useful features to be used by a classifier for prediction tasks ...
Knowledge Transfer in Reinforcement Learning: How agents should benefit from prior knowledge
Reinforcement learning (RL) has had many successes in different tasks, but in practice, it often requires significant amounts of data or training time to learn high-performing policies. For complicated tasks, the learning ...