In this paper we address the problem of discretization in the context of learning Bayesian networks (BNs) from data containing both continuous and discrete variables. We describe ...
Most research in learning for planning has concentrated on efficiency gains. Another important goal is improving the quality of final plans. Learning to improve plan quality has b...
—In this paper, we present a near ML-achieving sphere search technique that reduces the number of search operations significantly over existing sphere decoding (SD) algorithms. ...
In peer-to-peer (P2P) systems where individual peers must cooperate to process each other's requests, a useful metric for evaluating the system is how many remote requests ar...
Existing estimation approaches for spatial databases often rely on the assumption that data distribution in a small region is uniform, which seldom holds in practice. Moreover, the...