Sustainable resource management in many domains presents large continuous stochastic optimization problems, which can often be modeled as Markov decision processes (MDPs). To solv...
Computational models of grounded language learning have been based on the premise that words and concepts are learned simultaneously. Given the mounting cognitive evidence for conc...
— In this paper we present a structure theory for generalized linear dynamic factor models (GDFM’s). Emphasis is laid on the so-called zeroless case. GDFM’s provide a way of ...
Recently, a number of researchers have proposed spectral algorithms for learning models of dynamical systems—for example, Hidden Markov Models (HMMs), Partially Observable Marko...
In evolving applications, there is a need for the dynamic selection of algorithms or algorithm parameters. Such selection is hardly ever governed by exact theory, so intelligent r...