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20122022
most citedInformation-theoretic thresholds for community detection in sparse networks

44 citations · 84 across the 6 of their papers we have counts for

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6 papers · 1 filter

math.PR20222 cited

Lipschitz changes of variables via heat flow

Joe Neeman

We extend Caffarelli's contraction theorem, by proving that there exists a Lipschitz changes of variables between the Gaussian measure and certain perturbations of it. Our approach…

math.PR20171 cited

Noise Stability is computable and low dimensional

Anindya De, Elchanan Mossel, Joe Neeman

Questions of noise stability play an important role in hardness of approximation in computer science as well as in the theory of voting. In many applications, the goal is to find a…

math.PR201644 cited

Information-theoretic thresholds for community detection in sparse networks

Jess Banks, Cristopher Moore, Joe Neeman +1

We give upper and lower bounds on the information-theoretic threshold for community detection in the stochastic block model. Specifically, consider the symmetric stochastic block m…

math.PR2016

An interpolation proof of Ehrhard's inequality

Joe Neeman, Grigoris Paouris

We prove Ehrhard's inequality using interpolation along the Ornstein-Uhlenbeck semi-group. We also provide an improved Jensen inequality for Gaussian variables that might be of ind…

math.PR2016

Noise Stability and Correlation with Half Spaces

Elchanan Mossel, Joe Neeman

Benjamini, Kalai and Schramm showed that a monotone function is noise stable if and only if it is correlated with a half-space (a set of the form $\{x…

math.PR2012

Robust Optimality of Gaussian Noise Stability

Elchanan Mossel, Joe Neeman

We prove that under the Gaussian measure, half-spaces are uniquely the most noise stable sets. We also prove a quantitative version of uniqueness, showing that a set which is almos…