As real-world Bayesian networks continue to grow larger and more complex, it is important to investigate the possibilities for improving the performance of existing algorithms of ...
In constraint programming one models a problem by stating constraints on acceptable solutions. The constraint model is then usually solved by interleaving backtracking search and ...
Content analysis and citation analysis are two common methods in recommending system. Compared with content analysis, citation analysis can discover more implicitly related papers...
Markov random field models provide a robust formulation of low-level vision problems. Among the problems, stereo vision remains the most investigated field. The belief propagation...
We present an interactive algorithm to compute sound propagation paths for transmission, specular reflection and edge diffraction in complex scenes. Our formulation uses an adaptiv...
Anish Chandak, Christian Lauterbach, Micah T. Tayl...