Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
For a discrete-time finite-state Markov chain, we develop an adaptive importance sampling scheme to estimate the expected total cost before hitting a set of terminal states. This s...
Approximate reachability techniques trade o accuracy for the capacity to deal with bigger designs. Cho et al 4 proposed partitioning the set of state bits into mutually disjoint s...
Shankar G. Govindaraju, David L. Dill, Jules P. Be...
In earlier work we have introduced and explored a variety of different probabilistic models for the problem of answering selectivity queries posed to large sparse binary data set...
This paper describes a new algorithm for view volume culling. During an interactive walkthrough of a 3D scene, at any moment a large proportion of objects will be outside of the v...