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Graph cluster randomization: network exposure to multiple universes
Graph cluster randomization network exposure multiple universes
2013/6/17
A/B testing is a standard approach for evaluating the effect of online experiments; the goal is to estimate the `average treatment effect' of a new feature or condition by exposing a sample of the ove...
Statistical Analysis of Metric Graph Reconstruction
Metric Graph Filament Reconstruction Manifold Learning Minimax Esti-mation
2013/6/13
A metric graph is a 1-dimensional stratified metric space consisting of vertices and edges or loops glued together. Metric graphs can be naturally used to represent and model data that take the form o...
Interpreting Graph Cuts as a Max-Product Algorithm
Max-Product Interpreting Graph binary variable models
2011/6/16
The maximum a posteriori (MAP) con guration
of binary variable models with submodular
graph-structured energy functions
can be found eciently and exactly by graph
cuts. Max-product belief propaga...