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Leveraging semantically similar queries for ranking via combining representations


Jun 23, 2021
Hayden S. Helm, Marah Abdin, Benjamin D. Pedigo, Shweti Mahajan, Vince Lyzinski, Youngser Park, Amitabh Basu, Piali~Choudhury, Christopher M. White, Weiwei Yang, Carey E. Priebe


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Dynamic Silos: Modularity in intra-organizational communication networks during the Covid-19 pandemic


May 01, 2021
Jonathan Larson, Tiona Zuzul, Emily Cox Pahnke, Neha Parikh Shah, Patrick Bourke, Nicholas Caurvina, Fereshteh Amini, Youngser Park, Joshua Vogelstein, Jeffrey Weston, Christopher White, Carey E. Priebe

* 19 pages, 15 figures 

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Dynamic Silos: Modularity in intra-organizational communication networks before and during the Covid-19 pandemic


Apr 07, 2021
Jonathan Larson, Tiona Zuzul, Emily Cox Pahnke, Neha Parikh Shah, Patrick Bourke, Nicholas Caurvina, Fereshteh Amini, Youngser Park, Joshua Vogelstein, Jeffrey Weston, Christopher White, Carey E. Priebe

* 17 pages, 14 figues 

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Inducing a hierarchy for multi-class classification problems


Feb 20, 2021
Hayden S. Helm, Weiwei Yang, Sujeeth Bharadwaj, Kate Lytvynets, Oriana Riva, Christopher White, Ali Geisa, Carey E. Priebe


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Subgraph nomination: Query by Example Subgraph Retrieval in Networks


Jan 29, 2021
Al-Fahad M. Al-Qadhi, Carey E. Priebe, Hayden S. Helm, Vince Lyzinski

* 31 pages, 11 figures 

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A partition-based similarity for classification distributions


Nov 12, 2020
Hayden S. Helm, Ronak D. Mehta, Brandon Duderstadt, Weiwei Yang, Christoper M. White, Ali Geisa, Joshua T. Vogelstein, Carey E. Priebe


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A Simple Spectral Failure Mode for Graph Convolutional Networks


Oct 27, 2020
Carey E. Priebe, Cencheng Shen, Ningyuan Huang, Tianyi Chen


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On identifying unobserved heterogeneity in stochastic blockmodel graphs with vertex covariates


Jul 04, 2020
Cong Mu, Angelo Mele, Lingxin Hao, Joshua Cape, Avanti Athreya, Carey E. Priebe

* 14 pages, 8 figures 

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Learning to rank via combining representations


May 20, 2020
Hayden S. Helm, Amitabh Basu, Avanti Athreya, Youngser Park, Joshua T. Vogelstein, Michael Winding, Marta Zlatic, Albert Cardona, Patrick Bourke, Jonathan Larson, Chris White, Carey E. Priebe

* 10 pages, 4 figures 

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On the role of features in vertex nomination: Content and context together are better (sometimes)


May 06, 2020
Keith Levin, Carey E. Priebe, Vince Lyzinski


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A general approach to progressive learning


Apr 28, 2020
Joshua T. Vogelstein, Hayden S. Helm, Ronak D. Mehta, Jayanta Dey, Weiwei Yang, Bryan Tower, Will LeVine, Jonathan Larson, Chris White, Carey E. Priebe


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Learning 1-Dimensional Submanifolds for Subsequent Inference on Random Dot Product Graphs


Apr 17, 2020
Michael W. Trosset, Mingyue Gao, Minh Tang, Carey E. Priebe

* 20 pages 

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On Two Distinct Sources of Nonidentifiability in Latent Position Random Graph Models


Mar 31, 2020
Joshua Agterberg, Minh Tang, Carey E. Priebe


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Graph matching between bipartite and unipartite networks: to collapse, or not to collapse, that is the question


Feb 05, 2020
Jesús Arroyo, Carey E. Priebe, Vince Lyzinski


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The Exact Equivalence of Independence Testing and Two-Sample Testing


Oct 20, 2019
Cencheng Shen, Carey E. Priebe, Joshua T. Vogelstein

* 27 pages main + 7 pages appendix 

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Limit theorems for out-of-sample extensions of the adjacency and Laplacian spectral embeddings


Sep 29, 2019
Keith Levin, Fred Roosta, Minh Tang, Michael W. Mahoney, Carey E. Priebe

* Portions of this work originally appeared in ICML2018 as "Out-of-sample extension of graph adjacency spectral embedding" (accompanying technical report available at arXiv:1802.06307). This work extends the results of that earlier paper to a second graph embedding technique called the Laplacian spectral embedding and presents additional experiments 

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Spectral inference for large Stochastic Blockmodels with nodal covariates


Aug 18, 2019
Angelo Mele, Lingxin Hao, Joshua Cape, Carey E. Priebe


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Geodesic Learning via Unsupervised Decision Forests


Jul 05, 2019
Meghana Madhyastha, Percy Li, James Browne, Veronika Strnadova-Neeley, Carey E. Priebe, Randal Burns, Joshua T. Vogelstein


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Vertex Nomination, Consistent Estimation, and Adversarial Modification


May 15, 2019
Joshua Agterberg, Youngser Park, Jonathan Larson, Christopher White, Carey E. Priebe, Vince Lyzinski

* 37 pages, 8 figures 

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Simultaneous Dimensionality and Complexity Model Selection for Spectral Graph Clustering


Apr 05, 2019
Congyuan Yang, Carey E. Priebe, Youngser Park, David J. Marchette


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Maximum Likelihood Estimation and Graph Matching in Errorfully Observed Networks


Dec 26, 2018
Jesús Arroyo, Daniel L. Sussman, Carey E. Priebe, Vince Lyzinski


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Random Projection Forests


Oct 10, 2018
Tyler M. Tomita, James Browne, Cencheng Shen, Jesse L. Patsolic, Jason Yim, Carey E. Priebe, Randal Burns, Mauro Maggioni, Joshua T. Vogelstein

* 46 pages; submitted to Journal of Machine Learning Research for review on 09/26/2018 

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From Distance Correlation to Multiscale Graph Correlation


Sep 30, 2018
Cencheng Shen, Carey E. Priebe, Joshua T. Vogelstein

* 39 pages + Appendix 22 pages, 6 figures 

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Discovering and Deciphering Relationships Across Disparate Data Modalities


Sep 25, 2018
Cencheng Shen, Qing Wang, Eric Bridgeford, Carey E. Priebe, Mauro Maggioni, Joshua T. Vogelstein


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On a 'Two Truths' Phenomenon in Spectral Graph Clustering


Sep 07, 2018
Carey E. Priebe, Youngser Park, Joshua T. Vogelstein, John M. Conroy, Vince Lyzinski, Minh Tang, Avanti Athreya, Joshua Cape, Eric Bridgeford


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A statistical interpretation of spectral embedding: the generalised random dot product graph


Jul 29, 2018
Patrick Rubin-Delanchy, Carey E. Priebe, Minh Tang, Joshua Cape

* 25 pages; 7 figures 

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On consistent vertex nomination schemes


May 29, 2018
Vince Lyzinski, Keith Levin, Carey E. Priebe

* 29 pages, 4 figures 

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Seeded Graph Matching


Apr 10, 2018
Donniell E. Fishkind, Sancar Adali, Heather G. Patsolic, Lingyao Meng, Digvijay Singh, Vince Lyzinski, Carey E. Priebe

* 24 pages, 10 figures 

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