Learning Bayesian network structure from large-scale data sets, without any expertspecified ordering of variables, remains a difficult problem. We propose systematic improvements ...
The joint-sparse recovery problem aims to recover, from sets of compressed measurements, unknown sparse matrices with nonzero entries restricted to a subset of rows. This is an ex...
In this paper, we study strategies in incremental planning for ordering and grouping subproblems partitioned by the subgoals of a planning problem when each subproblem is solved b...
Abstract. The ability to cooperate on common tasks in a distributed setting is key to solving a broad range of computation problems ranging from distributed search such as SETI to ...
Chryssis Georgiou, Alexander Russell, Alexander A....
Data integrated from multiple sources may contain inconsistencies that violate integrity constraints. The constraint repair problem attempts to find "low cost" changes t...
Philip Bohannon, Michael Flaster, Wenfei Fan, Raje...