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Matrix Completion with Hierarchical Graph Side Information
We consider a matrix completion problem that exploits social or item similarity graphs as side information.
On the Fundamental Limits of Matrix Completion: Leveraging Hierarchical Similarity Graphs
In the achievability proof, we demonstrate that probability of error of the maximum likelihood estimator vanishes for sufficiently large number of users and items, if all sufficient conditions are satisfied.
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