Review for NeurIPS paper: Learning to Decode: Reinforcement Learning for Decoding of Sparse Graph-Based Channel Codes

Strengths: LDPC code is an indispensable building block for LTE/5G communication systems, a more efficient and accurate decoding algorithm is impactful for current communication systems. Node-wise scheduling (NS) is known to improve decoding efficiency, yet incurs more complexity. Using Q-learning Table the computation complexity improves, which makes the NS-based method become viable. The long block length nature of LDPC code, makes the number of state exponential. The author uses clustered based method to reduce the number of potential state.