In large data recording and warehousing environments, it is often advantageous to provide fast, approximate answers to queries, whenever possible. Before DBMSs providing highly-ac...
For many probability distributions of interest, it is quite difficult to obtain samples efficiently. Often, Markov chains are employed to obtain approximately random samples fro...
A common subproblem of DNF approximate counting and derandomizing RL is the discrepancy problem for combinatorial rectangles. We explicitly construct a poly(n)-size sample space t...
Roy Armoni, Michael E. Saks, Avi Wigderson, Shiyu ...
We show that an important and computationally challenging solution space feature of the graph coloring problem (COL), namely the number of clusters of solutions, can be accurately...
Rao–Blackwellization is an approximation technique for probabilistic inference that flexibly combines exact inference with sampling. It is useful in models where conditioning o...