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There is a large theoretical literature on methods for estimating causal effects under unconfoundedness, exogeneity, or selection-on-observables type assumptions using matching or propensity score met...
We propose a dynamic allocation procedure that increases power and efficiency when measuring an average treatment effect in sequential randomized trials. Subjects arrive iteratively and are either ran...
Matching patches from a noisy image to atoms in a dictionary of patches is a key ingredient to many techniques in image processing and computer vision. By representing with a single atom all patches t...
Matching patches from a noisy image to atoms in a dictionary of patches is a key ingredient to many techniques in image processing and computer vision. By representing with a single atom all patches t...
This article presents culture as a vehicle of labor market sorting. Providing a case study of hiring in elite professional service firms, I investigate the often suggested but heretofore empirically u...
We study algorithms for matching user tracks, consisting of time-ordered location points, to paths in the road network. Previous work has focused on the scenario where the location data is linearly or...
In this paper, we present coherence-based performance guarantees of Orthogonal Matching Pursuit (OMP) for both support recovery and signal reconstruction of sparse signals when the measurements are co...
Seeded Graph Matching     Seeded  Graph  Matching       2012/11/21
Graph inference is a burgeoning field in the applied and theoretical statistics communities, as well as throughout the wider world of science, engineering, business, etc. Given two graphs on the same ...
This paper investigates the detection of information hidden by the Least Significant Bit (LSB) matching scheme. In a theoretical context of known image media parameters, two important results are pres...
Given the output of a data source taking values in a finite alphabet, we wish to detect change-points, that is times when the statistical properties of the source change.
In this paper, we consider the problem of compressed sensing where the goal is to recover almost all the sparse vectors using a small number of fixed linear measurements. For this problem, we propose ...
The propensity score analysis is one of the most widely used methods for study- ing the causal treatment e ect in observational studies. This paper studies treatment e ect estimation with the method...
Orthogonal Matching Pursuit (OMP) has long been considered a powerful heuristic for attacking compressive sensing problems; however, its theoretical development is, unfortunately, somewhat lacking. Th...
The goal of cross-domain object matching (CDOM) is to find correspondence between two sets of objects in different domains in an unsupervised way. Photo album summarization is a typical application of...
Followership has been an understudied topic in the academic literature and an underappreciated topic among practitioners. Although it has always been important, the study of followership has beco...

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