Reduction of Maximum Entropy Models to Hidden Markov Models

We show that maximum entropy models can be modeled with certain kinds of Hidden Markov Models (HMMs). This allows us to easily construct maximum entropy models with hidden variables, hidden state sequences, or other characteristics. The resulting models can be easily trained using standard algorithms with guaranteed optimality.