We introduce a new technique that can reduce any
higher-order Markov random field with binary labels into
a first-order one that has the same minima as the original.
Moreover, w...
We study the problem of learning to accurately rank a set of objects by combining a given collection of ranking or preference functions. This problem of combining preferences aris...
Yoav Freund, Raj D. Iyer, Robert E. Schapire, Yora...
We introduce a theoretical framework for discovering relationships between two database instances over distinct and unknown schemata. This framework is grounded in the context of ...
This paper reports on a novel decentralised technique for planning agent schedules in dynamic task allocation problems. Specifically, we use a Markov game formulation of these pr...
Archie C. Chapman, Rosa Anna Micillo, Ramachandra ...
: It is well-known that constraint satisfaction problems (CSP) over an unbounded domain can be solved in time nO(k) if the treewidth of the primal graph of the instance is at most ...