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The loss surface of deep and wide neural networks

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cs.LG 1

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2019 1

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UNVERDICTED 1

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Exploring Model-based Planning with Policy Networks

cs.LG · 2019-06-20 · unverdicted · novelty 7.0

POPLIN combines policy networks with model-predictive planning by optimizing either action sequences or policy parameters, yielding 3x better sample efficiency than PETS, TD3 and SAC on MuJoCo locomotion tasks.

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  • Exploring Model-based Planning with Policy Networks cs.LG · 2019-06-20 · unverdicted · none · ref 30

    POPLIN combines policy networks with model-predictive planning by optimizing either action sequences or policy parameters, yielding 3x better sample efficiency than PETS, TD3 and SAC on MuJoCo locomotion tasks.