—Multistage stochastic programs are effective for solving long-term planning problems under uncertainty. Such programs are usually based on scenario generation model about future...
We study the problem of computing approximate quantiles in large-scale sensor networks communication-efficiently, a problem previously studied by Greenwald and Khana [12] and Shri...
We consider the problem of learning Gaussian multiresolution (MR) models in which data are only available at the finest scale and the coarser, hidden variables serve both to captu...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...
Dependency networks approximate a joint probability distribution over multiple random variables as a product of conditional distributions. Relational Dependency Networks (RDNs) are...
Sriraam Natarajan, Tushar Khot, Kristian Kersting,...
We describe a simple iterative method for proving a variety of results in combinatorial optimization. It is inspired by Jain’s iterative rounding method (FOCS 1998) for designing...