Two Bayesian-network structures are said to be equivalent if the set of distributions that can be represented with one of those structures is identical to the set of distributions...
Recently, manifold learning has been widely exploited in pattern recognition, data analysis, and machine learning. This paper presents a novel framework, called Riemannian manifold...
In many energy-constrained wireless sensor networks, nodes cooperatively forward correlated sensed data to data sinks. In order to reduce the communication cost (e.g. overall ener...
Junning Liu, Micah Adler, Donald F. Towsley, Chun ...
Recently the problem of dimensionality reduction has received a lot of interests in many fields of information processing. We consider the case where data is sampled from a low d...
We investigate the problem of learning to predict moves in the board game of Go from game records of expert players. In particular, we obtain a probability distribution over legal...