2018
N2N learning: Network to Network Compression via Policy Gradient Reinforcement Learning
ICLR 2018poster
While bigger and deeper neural network architectures continue to advance the state-of-the-art for many computer vision tasks, real-world adoption of these networks is impeded by hardware and speed constraints. Conventional model compression methods attempt to address this problem by modifying the ar…