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This paper is concerned with developing an information-theoretic framework to aggregate the state space of a Hidden Markov Model (HMM) on discrete state and observation spaces. The...
We study a method of optimal data-driven aggregation of classifiers in a convex combination and establish tight upper bounds on its excess risk with respect to a convex loss funct...