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APPROX
2005
Springer
14 years 2 months ago
2005
Springer
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
STOC
2005
ACM
14 years 9 months ago
2005
ACM
We introduce a new graph parameter, called the Grothendieck constant of a graph G = (V, E), which is defined as the least constant K such that for every A : E R, sup f:V S|V |-1 ...
ICALP
2009
Springer
14 years 9 months ago
2009
Springer
Estimating frequency moments and Lp distances are well studied problems in the adversarial data stream model and tight space bounds are known for these two problems. There has been...
SODA
2001
ACM
13 years 10 months ago
2001
ACM
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
ESA
2006
Springer
14 years 11 days ago
2006
Springer
An instance of the path hitting problem consists of two families of paths, D and H, in a common undirected graph, where each path in H is associated with a non-negative cost. We r...