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Sparse Canonical Correlation Analysis via Concave Minimization
Omid S. Solari, James B. Brown, Peter J. Bickel
A new approach to the sparse Canonical Correlation Analysis (sCCA)is proposed with the aim of discovering interpretable associations in very high-dimensional multi-view, i.e.observ…
Two provably consistent divide and conquer clustering algorithms for large networks
Soumendu Sundar Mukherjee, Purnamrita Sarkar, Peter J. Bickel
In this article, we advance divide-and-conquer strategies for solving the community detection problem in networks. We propose two algorithms which perform clustering on a number of…
Community Detection in Networks using Graph Distance
Sharmodeep Bhattacharyya, Peter J. Bickel
The study of networks has received increased attention recently not only from the social sciences and statistics but also from physicists, computer scientists and mathematicians. O…
Hypothesis Testing for Automated Community Detection in Networks
Peter J. Bickel, Purnamrita Sarkar
Community detection in networks is a key exploratory tool with applications in a diverse set of areas, ranging from finding communities in social and biological networks to identif…
Role of normalization in spectral clustering for stochastic blockmodels
Purnamrita Sarkar, Peter J. Bickel
Spectral clustering is a technique that clusters elements using the top few eigenvectors of their (possibly normalized) similarity matrix. The quality of spectral clustering is clo…
Large Vector Auto Regressions
Song Song, Peter J. Bickel
One popular approach for nonstructural economic and financial forecasting is to include a large number of economic and financial variables, which has been shown to lead to signific…