We consider the problem of structured classification, where the task is to predict a label y from an input x, and y has meaningful internal structure. Our framework includes super...
Peter L. Bartlett, Michael Collins, Benjamin Taska...
Log-concavity is an important property in the context of optimization, Laplace approximation, and sampling; Bayesian methods based on Gaussian process priors have become quite pop...
We present a simple, easily implemented spectral learning algorithm which applies equally whether we have no supervisory information, pairwise link constraints, or labeled example...
Sepandar D. Kamvar, Dan Klein, Christopher D. Mann...
We present a new class of games, local-effect games (LEGs), which exploit structure in a different way from other compact game representations studied in AI. We show both theoreti...
Traditional algorithms for prime implicate generation [Quine, 1952; McCluskey, 1956; Tison, 1967; Kean and Tsiknis, 1990; de Kleer, 1992] require the input formulas to be first tr...