Pierre-Luc Bacon

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Deep learning has become the state-of-art tool in many applications, but the evaluation and training of deep models can be time-consuming and computationally expensive. The conditional computation approach has been proposed to tackle this problem (Bengio et al., 2013; Davis & Arel, 2013). It operates by selectively activating only parts of the network at a(More)
We consider the problem of learning and planning in Markov decision processes with temporally extended actions represented in the options framework. We propose to use predictions about the duration of extended actions to represent the state and show that this leads to a compact pre-dictive state representation model independent of the set of primitive(More)
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