We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows that the class of factor graphs with bounded degree...
To automatically register foreground target in cluttered images, we present a novel hierarchical graph representation and a stochastic computing strategy in Bayesian framework. Th...
Xiaobai Liu, Liang Lin, Hongwei Li, Hai Jin, Wenbi...
This work proposes and evaluates a sampling algorithm based on wavelet transforms with Coiflets basis to reduce the data sensed in wireless sensor networks applications. The Coi...
A partition of a set of n items is a grouping of the items into k disjoint classes of equal size. Any partition can be modeled as a graph: the items become the vertices of the grap...
We present a unified framework for designing polynomial time approximation schemes (PTASs) for “dense” instances of many NP-hard optimization problems, including maximum cut,...