The Inductive Logic Programming community has considered proof-complexity and model-complexity, but, until recently, size-complexity has received little attention. Recently a chal...
Abstract. We develop a Bayesian approach to concept learning for crowdsourcing applications. A probabilistic belief over possible concept definitions is maintained and updated acc...
Paolo Viappiani, Sandra Zilles, Howard J. Hamilton...
We investigate the application of Courcelle’s Theorem and the logspace version of Elberfeld et al. in the context of the implication problem for propositional sets of formulae, t...
Arne Meier, Johannes Schmidt, Michael Thomas, Heri...
We address complexity issues for linear differential equations in characteristic p > 0: resolution and computation of the p-curvature. For these tasks, our main focus is on al...
The paper takes a fresh look at algorithms for maximizing expected utility over a set of policies, that is, a set of possible ways of reacting to observations about an uncertain s...