
Causal Inference under Network Interference with Noise
Increasingly, there is a marked interest in estimating causal effects un...
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BiasVariance Tradeoffs in Joint Spectral Embeddings
Latent position models and their corresponding estimation procedures off...
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Estimation of the Epidemic Branching Factor in Noisy Contact Networks
Many fundamental concepts in networkbased epidemic models depend on the...
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Maximum Likelihood Estimation and Graph Matching in Errorfully Observed Networks
Given a pair of graphs with the same number of vertices, the inexact gra...
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Tractable Graph Matching via Soft Seeding
The graph matching problem aims to discover a latent correspondence betw...
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Matched Filters for Noisy Induced Subgraph Detection
We consider the problem of finding the vertex correspondence between two...
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Statistical inference on random dot product graphs: a survey
The random dot product graph (RDPG) is an independentedge random graph ...
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Law of Large Graphs
Estimating the mean of a population of graphs based on a sample is a cor...
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Analyzing statistical and computational tradeoffs of estimation procedures
The recent explosion in the amount and dimensionality of data has exacer...
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Empirical Bayes Estimation for the Stochastic Blockmodel
Inference for the stochastic blockmodel is currently of burgeoning inter...
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Spectral Clustering for DivideandConquer Graph Matching
We present a parallelized bijective graph matching algorithm that levera...
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A central limit theorem for scaled eigenvectors of random dot product graphs
We prove a central limit theorem for the components of the largest eigen...
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Universally consistent vertex classification for latent positions graphs
In this work we show that, using the eigendecomposition of the adjacenc...
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Statistical inference on errorfully observed graphs
Statistical inference on graphs is a burgeoning field in the applied and...
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Universally Consistent Latent Position Estimation and Vertex Classification for Random Dot Product Graphs
In this work we show that, using the eigendecomposition of the adjacenc...
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A consistent adjacency spectral embedding for stochastic blockmodel graphs
We present a method to estimate block membership of nodes in a random gr...
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Daniel L. Sussman
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Assistant Professor in the Department of Mathematics and Statistics at Boston University