An important class of heuristics for constraint satisfaction problems works by sampling information during search in order to inform subsequent decisions. One of these strategies, ...
We study approximations of optimization problems with probabilistic constraints in which the original distribution of the underlying random vector is replaced with an empirical dis...
In this paper we address the problem of detecting topics in large-scale linked document collections. Recently, topic detection has become a very active area of research due to its...
Geometric constraint solving is a key issue in CAD/CAM. Since Owen’s seminal paper, solvers typically use graph based decomposition methods. However, these methods become diffi...
Despite the recent advances in distributed MDP frameworks for reasoning about multiagent teams, these frameworks mostly do not reason about resource constraints, a crucial issue i...
Praveen Paruchuri, Milind Tambe, Fernando Ord&oacu...