This work compresses reinforcement learning models for Atari games, improving localization.
problem Expensive deep neural networks in reinforcement learning.
method Model compression, global max-pooling, Actor-Mimic, weakly supervised localization.
result Compression reduces model size to 3% of original, enabling object localization.