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» Reconstruction for Models on Random Graphs
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FOCS
2007
IEEE
13 years 11 months ago
Reconstruction for Models on Random Graphs
Consider a collection of random variables attached to the vertices of a graph. The reconstruction problem requires to estimate one of them given ‘far away’ observations. Sever...
Antoine Gerschenfeld, Andrea Montanari
APPROX
2008
Springer
119views Algorithms» more  APPROX 2008»
13 years 7 months ago
The Complexity of Distinguishing Markov Random Fields
Abstract. Markov random fields are often used to model high dimensional distributions in a number of applied areas. A number of recent papers have studied the problem of reconstruc...
Andrej Bogdanov, Elchanan Mossel, Salil P. Vadhan
FCT
2005
Springer
13 years 10 months ago
Reconstructing Many Partitions Using Spectral Techniques
A partitioning of a set of n items is a grouping of these items into k disjoint, equally sized classes. Any partition can be modeled as a graph. The items become the vertices of th...
Joachim Giesen, Dieter Mitsche
CORR
2011
Springer
152views Education» more  CORR 2011»
13 years 8 days ago
Topology Discovery of Sparse Random Graphs With Few Participants
We consider the task of topology discovery of sparse random graphs using end-to-end random measurements (e.g., delay) between a subset of nodes, referred to as the participants. T...
Animashree Anandkumar, Avinatan Hassidim, Jonathan...
ISAAC
2005
Springer
111views Algorithms» more  ISAAC 2005»
13 years 10 months ago
Boosting Spectral Partitioning by Sampling and Iteration
A partition of a set of n items is a grouping of the items into k disjoint classes of equal size. Any partition can be modeled as a graph: the items become the vertices of the grap...
Joachim Giesen, Dieter Mitsche