S
Sourav Chatterjee
Researcher at Stanford University
Publications - 191
Citations - 8553
Sourav Chatterjee is an academic researcher from Stanford University. The author has contributed to research in topics: Central limit theorem & Gaussian. The author has an hindex of 43, co-authored 171 publications receiving 7372 citations. Previous affiliations of Sourav Chatterjee include New York University & University of California.
Papers
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Spectral clustering and the high-dimensional stochastic blockmodel
TL;DR: In this article, the authors studied spectral clustering under the stochastic block model and showed that the eigenvectors of the normalized graph Laplacian asymptotically converges to the eigens of a population normalized graph.
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Spectral clustering and the high-dimensional stochastic blockmodel
TL;DR: The asymptotic results in th is paper are the first clustering results that allow the number of clusters in the model to grow with theNumber of nodes, hence the name high-dimensional.
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Matrix estimation by Universal Singular Value Thresholding
TL;DR: This paper introduces a simple estimation procedure, called Universal Singular Value Thresholding (USVT), that works for any matrix that has "a little bit of structure" and achieves the minimax error rate up to a constant factor.
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Matrix estimation by Universal Singular Value Thresholding
TL;DR: The Universal Singular Value Thresholding (USVT) estimator as discussed by the authors achieves the minimax error rate up to a constant factor for any matrix that has a little bit of structure.
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Estimating and understanding exponential random graph models
Sourav Chatterjee,Persi Diaconis +1 more
TL;DR: In this paper, the authors introduce a method for the theoretical analysis of exponential random graph models based on a large deviation approximation to the normalizing constant shown to be consistent using theory developed by Chatterjee and Varadhan [European J. Combin. 32 (2011) 1000-1017].