Reviews: Discriminative State Space Models

Based on these bounds, a structural risk minimization formulation is proposed to estimate forecasting models with learning guarantees both in the case where the state-space predictor is not neccesarily accurate and in the case where we assume that it is. The authors show that for many models of interest, this is a reasonable assumption. The convex objective function of the resulting SRM is then solved using a coordinate descent algorithm, with some encouraging empirical results presented in the appendix.