We introduce novel results for approximate inference on planar graphical models using the loop calculus framework. The loop calculus (Chertkov and Chernyak, 2006b) allows to expre...
Multiple memory module architecture offers higher performance by providing potentially doubled memory bandwidth. Two key problems in gaining high performance in this kind of archi...
Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...
A promising approach to graph clustering is based on the intuitive notion of intra-cluster density vs. inter-cluster sparsity. While both formalizations and algorithms focusing on ...
In this paper, we describe two new ideas by which HPF compiler can deal with irregular computations e ectively. The rst mechanism invokes a user speci ed mapping procedure via a s...