We focus on the problem of efficient learning of dependency trees. Once grown, they can be used as a special case of a Bayesian network, for PDF approximation, and for many other u...
In this paper, we provide a study on the use of tree kernels to encode syntactic parsing information in natural language learning. In particular, we propose a new convolution kerne...
We present a junction tree decomposition based algorithm for parallel exact inference. This is a novel parallel exact inference method for evidence propagation in an arbitrary jun...
For specifying and verifying branching-time requirements, a reactive system is traditionally modeled as a labeled tree, where a path in the tree encodes a possible execution of the...
We propose a more robust robot programming by demonstration system planner that produces a reproduction path which satisfies statistical constraints derived from demonstration traj...