This paper explores the relation between the structured parallelism exposed by the Decomposable BSP (DBSP) model through submachine locality and locality of reference in multi-lev...
Andrea Pietracaprina, Geppino Pucci, Francesco Sil...
We present a data-driven approach to predict the importance of edges and construct a Markov network for image analysis based on statistical models of global and local image feature...
We address in this paper the problem of segmenting complex handritten pages such as novelist drafts or authorial manuscripts. We propose to use stochastic and contextual models in...
We present a novel dual decomposition approach to MAP inference with highly connected discrete graphical models. Decompositions into cyclic k-fan structured subproblems are shown t...
A novel procedure is presented to construct image-domain filters (receptive fields) that directly recover local motion and shape parameters. These receptive fields are derived fro...