Efficient Decoupled Neural Architecture Search By Structure And Operation Sampling

We propose a novel neural architecture search algorithm via reinforcement learning by decoupling structure and operation search. Our approach samples candidate models from the multinomial distribution over the policy vectors. The proposed technique improv
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