We give tight bounds on the parallel complexity of some problems involving random graphs. Speci cally, we show that a Hamiltonian cycle, a breadth rst spanning tree, and a maximal...
We propose a sequential randomized algorithm, which at each step concentrates on functions having both low risk and low variance with respect to the previous step prediction functi...
We seek to both detect and segment objects in images. To exploit both local image data as well as contextual information, we introduce Boosted Random Fields (BRFs), which use boos...
Antonio Torralba, Kevin P. Murphy, William T. Free...
Conditional random fields for sequence labeling offer advantages over both generative models like HMMs and classifiers applied at each sequence position. Among sequence labeling...
We consider a model where commodity service providers are offering commodity computational services to a set of customers. We provide a solution for the efficient distribution of ...