Search Results for author: Carey Priebe

Found 12 papers, 3 papers with code

Edge-Parallel Graph Encoder Embedding

1 code implementation6 Feb 2024 Ariel Lubonja, Cencheng Shen, Carey Priebe, Randal Burns

New algorithms for embedding graphs have reduced the asymptotic complexity of finding low-dimensional representations.

Bilingual Lexicon Induction for Low-Resource Languages using Graph Matching via Optimal Transport

no code implementations25 Oct 2022 Kelly Marchisio, Ali Saad-Eldin, Kevin Duh, Carey Priebe, Philipp Koehn

Bilingual lexicons form a critical component of various natural language processing applications, including unsupervised and semisupervised machine translation and crosslingual information retrieval.

Bilingual Lexicon Induction Graph Matching +3

Nonparametric Two-Sample Hypothesis Testing for Random Graphs with Negative and Repeated Eigenvalues

no code implementations17 Dec 2020 Joshua Agterberg, Minh Tang, Carey Priebe

We propose a nonparametric two-sample test statistic for low-rank, conditionally independent edge random graphs whose edge probability matrices have negative eigenvalues and arbitrarily close eigenvalues.

Graph Embedding Statistics Theory Statistics Theory

Spectral embedding of weighted graphs

no code implementations12 Oct 2019 Ian Gallagher, Andrew Jones, Anna Bertiger, Carey Priebe, Patrick Rubin-Delanchy

When analyzing weighted networks using spectral embedding, a judicious transformation of the edge weights may produce better results.

Anomaly Detection Clustering +1

Sparse Representation Classification via Screening for Graphs

no code implementations4 Jun 2019 Cencheng Shen, Li Chen, Yuexiao Dong, Carey Priebe

The sparse representation classifier (SRC) is shown to work well for image recognition problems that satisfy a subspace assumption.

Classification Classification Consistency +1

Vertex nomination: The canonical sampling and the extended spectral nomination schemes

no code implementations14 Feb 2018 Jordan Yoder, Li Chen, Henry Pao, Eric Bridgeford, Keith Levin, Donniell Fishkind, Carey Priebe, Vince Lyzinski

There are vertex nomination schemes in the literature, including the optimally precise canonical nomination scheme~$\mathcal{L}^C$ and the consistent spectral partitioning nomination scheme~$\mathcal{L}^P$.

Clustering Stochastic Block Model

Active Community Detection in Massive Graphs

2 code implementations30 Dec 2014 Heng Wang, Da Zheng, Randal Burns, Carey Priebe

A canonical problem in graph mining is the detection of dense communities.

Social and Information Networks Physics and Society

Techniques for clustering interaction data as a collection of graphs

no code implementations24 Jun 2014 Nam H. Lee, Carey Priebe, Youngser Park, I-Jeng Wang, Michael Rosen

A natural approach to analyze interaction data of form "what-connects-to-what-when" is to create a time-series (or rather a sequence) of graphs through temporal discretization (bandwidth selection) and spatial discretization (vertex contraction).

Clustering Community Detection +3

Robust Vertex Classification

no code implementations23 Nov 2013 Li Chen, Cencheng Shen, Joshua Vogelstein, Carey Priebe

For random graphs distributed according to stochastic blockmodels, a special case of latent position graphs, adjacency spectral embedding followed by appropriate vertex classification is asymptotically Bayes optimal; but this approach requires knowledge of and critically depends on the model dimension.

Classification General Classification +1

Perfect Clustering for Stochastic Blockmodel Graphs via Adjacency Spectral Embedding

no code implementations2 Oct 2013 Vince Lyzinski, Daniel Sussman, Minh Tang, Avanti Athreya, Carey Priebe

Vertex clustering in a stochastic blockmodel graph has wide applicability and has been the subject of extensive research.

Clustering

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