  In this paper, we study the tradeoffs between complexity and reliability for
decoding large linear block codes. We show that using artificial neural
networks to predict the required order of an ordered statistics based decoder
helps in reducing the average complexity and hence the latency of the decoder.
We numerically validate the approach through Monte Carlo simulations.
