Metacontrol for Adaptive Imagination-Based Optimization

7 May 2017Jessica B. HamrickAndrew J. BallardRazvan PascanuOriol VinyalsNicolas HeessPeter W. Battaglia

Many machine learning systems are built to solve the hardest examples of a particular task, which often makes them large and expensive to run---especially with respect to the easier examples, which might require much less computation. For an agent with a limited computational budget, this "one-size-fits-all" approach may result in the agent wasting valuable computation on easy examples, while not spending enough on hard examples... (read more)

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