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Inference in Graphical Models via Semidefinite Programming Hierarchies
Murat A. Erdogdu, Yash Deshpande, Andrea Montanari
Maximum A posteriori Probability (MAP) inference in graphical models amounts to solving a graph-structured combinatorial optimization problem. Popular inference algorithms such as…
Learning Combinations of Sigmoids Through Gradient Estimation
Stratis Ioannidis, Andrea Montanari
We develop a new approach to learn the parameters of regression models with hidden variables. In a nutshell, we estimate the gradient of the regression function at a set of random…
Fundamental Limits of Weak Recovery with Applications to Phase Retrieval
Marco Mondelli, Andrea Montanari
In phase retrieval we want to recover an unknown signal from quadratic measurements of the form $y_i = |\langle{\boldsymbol a}_i,{\boldsymbol x}\r…
Non-negative Matrix Factorization via Archetypal Analysis
Hamid Javadi, Andrea Montanari
Given a collection of data points, non-negative matrix factorization (NMF) suggests to express them as convex combinations of a small set of `archetypes' with non-negative entries.…