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APPROX
2005
Springer
111views Algorithms» more  APPROX 2005»
15 years 11 months ago
Sampling Bounds for Stochastic Optimization
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...
Moses Charikar, Chandra Chekuri, Martin Pál
FSTTCS
2008
Springer
15 years 7 months ago
Pruning 2-Connected Graphs
Given an edge-weighted undirected graph G with a specified set of terminals, let the density of any subgraph be the ratio of its weight/cost to the number of terminals it contain...
Chandra Chekuri, Nitish Korula
IJCAI
2003
15 years 7 months ago
Probabilistically Survivable MASs
Muhiagent systems (MAS) can "go down" for a large number of reasons, ranging from system malfunctions and power failures to malicious attacks. The placement of agents on...
Sarit Kraus, V. S. Subrahmanian, N. Cihan Tas
WWW
2011
ACM
15 years 1 months ago
Limiting the spread of misinformation in social networks
In this work, we study the notion of competing campaigns in a social network. By modeling the spread of influence in the presence of competing campaigns, we provide necessary too...
Ceren Budak, Divyakant Agrawal, Amr El Abbadi
UAI
2001
15 years 7 months ago
Iterative Markov Chain Monte Carlo Computation of Reference Priors and Minimax Risk
We present an iterative Markov chain Monte Carlo algorithm for computing reference priors and minimax risk for general parametric families. Our approach uses MCMC techniques based...
John D. Lafferty, Larry A. Wasserman