Gradient computation in linear-chain conditional random fields using the entropy message passing algorithm

The paper proposes a numerically stable recursive algorithm for the exact computation of the linear-chain conditional random field gradient. It operates as a forward algorithm over the log-domain expectation semiring and has the purpose of enhancing memory efficiency when applied to long observation sequences. Unlike the traditional algorithm based on the forward–backward recursions, the memory complexity of our algorithm does not depend on the sequence length. The experiments on real data show that it can be useful for the problems which deal with long sequences.

► The memory complexity of the EMP algorithm does not depend on the sequence length. ► The EMP computational complexity is the same as the standard algorithm. ► The algorithm is useful in the long sequence labeling tasks.