We propose efficient particle smoothing methods for generalized state-spaces models. Particle smoothing is an expensive O(N2 ) algorithm, where N is the number of particles. We ov...
Mike Klaas, Mark Briers, Nando de Freitas, Arnaud ...
Recent theoretical results have shown that improved bounds on generalization error of classifiers can be obtained by explicitly taking the observed margin distribution of the trai...
Recently, Balcan and Blum [1] suggested a theory of learning based on general similarity functions, instead of positive semi-definite kernels. We study the gap between the learnin...
Systems development research shows that practitioners seldom follow methods and that the competencies required for successful development of computer-based systems go well beyond t...
In this work, we improve on existing work that studied the relationship between the proof system of modern SAT solvers and general resolution. Previous contributions such as those ...