—In graph-based learning models, entities are often represented as vertices in an undirected graph with weighted edges describing the relationships between entities. In many real...
During the past few years, point-based POMDP solvers have gradually scaled up to handle medium sized domains through better selection of the set of points and efficient backup met...
Guy Shani, Pascal Poupart, Ronen I. Brafman, Solom...
This paper presents a sequential state estimation method with arbitrary probabilistic models expressing the system’s belief. Probabilistic models can be estimated by Maximum a po...
In this paper, we study the problem of learning block classification models to estimate block functions. We distinguish general models, which are learned across multiple sites, an...
This paper revisits the lattice-based thesaurus models which Margaret Masterman used for machine translation in the 1950’s and 60’s. Masterman’s notions are mapped onto moder...