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» On the Approximability of the Steiner Tree Problem
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WCE
2007
13 years 8 months ago
Scenario Generation Employing Copulas
—Multistage stochastic programs are effective for solving long-term planning problems under uncertainty. Such programs are usually based on scenario generation model about future...
Kristina Sutiene, Henrikas Pranevicius
SIGMOD
2011
ACM
206views Database» more  SIGMOD 2011»
12 years 10 months ago
Sampling based algorithms for quantile computation in sensor networks
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...
Zengfeng Huang, Lu Wang, Ke Yi, Yunhao Liu
TSP
2010
13 years 2 months ago
Gaussian multiresolution models: exploiting sparse Markov and covariance structure
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...
ML
2012
ACM
413views Machine Learning» more  ML 2012»
12 years 3 months ago
Gradient-based boosting for statistical relational learning: The relational dependency network case
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,...
FSTTCS
2009
Springer
14 years 2 months ago
Iterative Methods in Combinatorial Optimization
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...
R. Ravi