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Collaborating Authors

 Chi-Ning Chou


(Nearly) Efficient Algorithms for the Graph Matching Problem on Correlated Random Graphs

Neural Information Processing Systems

We give the first efficient algorithms proven to succeed in the correlated Erdös-Rényi model (Pedarsani and Grossglauser, 2011). Specifically, we give a polynomial time algorithm for the graph similarity/hypothesis testing task which works for every constant level of correlation between the two graphs that can be arbitrarily close to zero.


(Nearly) Efficient Algorithms for the Graph Matching Problem on Correlated Random Graphs

Neural Information Processing Systems

We give the first efficient algorithms proven to succeed in the correlated Erdös-Rényi model (Pedarsani and Grossglauser, 2011). Specifically, we give a polynomial time algorithm for the graph similarity/hypothesis testing task which works for every constant level of correlation between the two graphs that can be arbitrarily close to zero.