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06/27/2022
Measures of independence and functional dependence
We follow up on Shi et al's (2020) and Cao's and my (2020) work on the l...
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11/27/2021
Learning from learning machines: a new generation of AI technology to meet the needs of science
We outline emerging opportunities and challenges to enhance the utility ...
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09/06/2021
Semiparametric Estimation of Treatment Effects in Randomized Experiments
We develop new semiparametric methods for estimating treatment effects. ...
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07/29/2021
Binomial Mixture Model With U-shape Constraint
In this article, we study the binomial mixture model under the regime th...
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02/25/2021
Interpretable Sensitivity Analysis for Balancing Weights
Assessing sensitivity to unmeasured confounding is an important step in ...
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08/24/2020
Correlations with tailored extremal properties
Recently, Chatterjee has introduced a new coefficient of correlation whi...
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09/17/2019
Sparse Canonical Correlation Analysis via Concave Minimization
A new approach to the sparse Canonical Correlation Analysis (sCCA)is pro...
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07/13/2019
An Assumption-Free Exact Test For Fixed-Design Linear Models With Exchangeable Errors
We propose the cyclic permutation test (CPT) to test general linear hypo...
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11/25/2018
Generalized R^2 Measures for a Mixture of Bivariate Linear Dependences
Motivated by the pressing needs for capturing complex but interperetable...
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10/02/2018
Hierarchical community detection by recursive bi-partitioning
The problem of community detection in networks is usually formulated as ...
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08/18/2017
Two provably consistent divide and conquer clustering algorithms for large networks
In this article, we advance divide-and-conquer strategies for solving th...
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08/07/2015
Spectral Clustering and Block Models: A Review And A New Algorithm
We focus on spectral clustering of unlabeled graphs and review some resu...
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01/16/2014
Community Detection in Networks using Graph Distance
The study of networks has received increased attention recently not only...
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11/12/2013
Hypothesis Testing for Automated Community Detection in Networks
Community detection in networks is a key exploratory tool with applicati...
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10/05/2013
Role of normalization in spectral clustering for stochastic blockmodels
Spectral clustering is a technique that clusters elements using the top ...
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07/10/2012
Pseudo-likelihood methods for community detection in large sparse networks
Many algorithms have been proposed for fitting network models with commu...
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06/20/2011
Large Vector Auto Regressions
One popular approach for nonstructural economic and financial forecastin...
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05/29/2007
