While known algorithms for sensitivity analysis and parameter tuning in probabilistic networks have a running time that is exponential in the size of the network, the exact comput...
An important theoretical tool in machine learning is the bias/variance decomposition of the generalization error. It was introduced for the mean square error in [3]. The bias/vari...
In this paper we develop an open queueing network for optimal design of multi-stage assemblies, in which each service station represents a manufacturing or assembly operation. The...
Amir Azaron, Hideki Katagiri, Kosuke Kato, Masatos...
We present a new phrase-based conditional exponential family translation model for statistical machine translation. The model operates on a feature representation in which sentenc...
We introduce H -join decompositions of graphs, indexed by a fixed bipartite graph H . These decompositions are based on a graph operation that we call H -join, which adds edges be...
Binh-Minh Bui-Xuan, Jan Arne Telle, Martin Vatshel...