Gradient Computation In Linear-Chain Conditional Random Fields Using The Entropy Message Passing Algorithm

The paper proposes a new recursive algorithm for the exact computation of the linear chain conditional random fields gradient. The algorithm is an instance of the Entropy Message Passing (EMP), introduced in our previous work, and has the purpose to enhance memory efficiency when applied to long observation sequences. Unlike the traditional algorithm based on the forward and the backward recursions, the memory complexity of our algorithm does not depend on the sequence length, having the same computational complexity as the standard algorithm.