Priebe, Carey E.

Professor
Applied Mathematics And Statistics
http://www.ams.jhu.edu/~priebe/

Whitehead Hall 201
cep@jhu.edu

Jump to:

News

Carey Priebe

Mapping the brain, neuron by neuron

August 10, 2017

Johns Hopkins engineers and an international team of neuroscientists created a complete map of the learning and memory center of the fruit fly larva brain, an early step toward mapping how all animal brains work.

Read More

About

Education
  • Ph.D. 1993, GEORGE MASON UNIVERSITY
Experience
  • 2007 - 2009:  Vice President, International Association for Statistical Computing
  • 2003 - 2004:  Chair, American Statistical Association (ASA)Section on Statistical Computing
  • 2003 - 2009:  Chair, Graduate Admissions Committee, Department of Applied Mathematics and Statistics, The Johns Hopkins University
  • Present:  Chair, IASC Program
  • Present:  Chair, Institute of Mathematical Statistics (IMS) New Researchers Committee
  • Present:  Secretary, Maryland Chapter of the American Statistical Association
  • Present:  Chair, IMS
Research Areas
  • COMPUTATIONAL statistics
  • Dimensionality reduction
  • Kernel and mixture estimates
  • Model selection
  • Statistical image analysis
  • Statistical inference for high-dimensional and graph data
  • Statsitical pattern recognition
Awards
  • 2018:  Office of Naval Research Young Investigator Award
  • 2018:  Oraculum Award for Excellence in Teaching - The Johns Hopkins University
  • 2018:  Outstanding Ph.D. Dissertation in Statistical Sciences Award - George Mason University
  • 2018:  Six U.S. patents
  • 2008:  Erskine Fellow - University of Canterbury - Christchurch - New Zealand - 2009
  • 2008:  National Security Science and Engineering Faculty Fellow - 2008
  • 2008:  Research Professor in the National Security Institute at the Naval Postgraduate School
  • 2008:  Robert B. Pond - Sr. - Excellence in Teaching Award - 2008
  • 2008:  Senior Member of the IEEE (Elected 2008)
  • 2007:  Elected Vice President of the International Association for Statistical Computing - 2007-2009
  • 2007:  Elected Member of the International Statistical Institute(Elected 2007)
  • 2006:  Exceptional Service to the American Statistical Association's Defense and Security Task Force - from Sallie Keller-McNulty - ASA President
  • 2006:  Keynote Speaker - 2006 Army Conference on Applied Statistics
  • 2002:  Fellow of the American Statistical Association (Elected 2002)
  • 2002:  National Security Agency Advisory Board Mathematics Panel
  • 2000:  ASEE Sabattical Leave Fellow
Presentations
  • "Limit Theorems for Eigenvectors of the Normalized Laplacian for Random Graphs", Theoretical Foundations for Statistical Network Analysis.  Cambridge, England.  October 6, 2016
  • "Semiparametric Spectral Modeling of the Drosophila Connectome", Theoretical Foundations for Statistical Network Analysis.  Cambridge, England.  August 22, 2016
  • "Repeated Motif Hierarchical Stochastic Blockmodels", Graph Limits and Statistics.  Cambridge, England.  July 15, 2016
  • "Community Detection and Classification in Hierarchical Stochastic Blockmodels".  England.  May 6, 2016
  • "Community Detection and Classification in Hierarchical Stochastic Blockmodels".  London, England.  April 29, 2016

Publications

Journal Articles
  • Shen C, Priebe C, Maggioni M, Vogelstein J (2018).  Discovering relationships across disparate data modalities.
  • Zheng D, Mhembere D, Vogelstein JT, Priebe CE, Burns R (2018).  FlashR: Parallelize and scale R for machine learning using SSDs.  Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP.  Part F134485.
  • Levin K, Athreya A, Tang M, Lyzinski V, Priebe CE (2017).  A central limit theorem for an omnibus embedding of multiple random dot product graphs.  IEEE International Conference on Data Mining Workshops, ICDMW.  2017-November.
  • Lyzinski V, Levin K, Priebe C (2017).  On consistent vertex nomination schemes.
  • Tang M, Cape J, Priebe C (2017).  Asymptotically efficient estimators for stochastic blockmodels: the naive MLE, the rank-constrained MLE, and the spectral.
  • Shen C, Priebe C, Vogelstein J (2017).  From distance correlation to multiscale generalized correlation.
  • Lyzinski V, Park Y, Priebe CE, Trosset M (2017).  Fast Embedding for JOFC Using the Raw Stress Criterion.  Journal of Computational and Graphical Statistics.  (4).
  • Qin Y, Priebe CE (2017).  Robust hypothesis testing via Lq-likelihood.  Statistica Sinica.  27(4).
  • Rubin-Delanchy P, Priebe C, Tang M (2017).  The generalized random dot product graph.
  • Athreya A, Fishkind D, Levin K, Lyzinski V, Park Y, Qin Y, Sussman D, Tang M, Vogelstein J, Priebe C (2017).  Statisical inference on random dot product graphs: a survey.  Journal of Machine Learning Research.
  • Yoder J, Priebe CE (2017).  Semi-supervised k-means++.  Journal of Statistical Computation and Simulation.  87(13).
  • Eichler K, Li F, Litwin-Kumar A, Park Y, Andrade I, Schneider-Mizell CM, Saumweber T, Huser A, Eschbach C, Gerber B, Fetter RD, Truman JW, Priebe CE, Abbott LF, Thum AS, Zlatic M, Cardona A (2017).  The complete connectome of a learning and memory centre in an insect brain.  Nature.  548(7666).
  • Tang M, Athreya A, Sussman DL, Lyzinski V, Priebe CE (2017).  A nonparametric two-sample hypothesis testing problem for random graphs.  Bernoulli.  23(3).
  • Patsolic H, Park Y, Lyzinski V, Priebe C (2017).  Vertex nomination via local neighborhood matching.
  • Levin K, Athreya A, Tang M, Lyzinski V, Priebe C (2017).  A central limit theorem for an omnibus embedding of random dot product graphs.
  • Tang R, Tang M, Vogelstein J, Priebe C (2017).  Robust estimation from multiple graphs under gross error contamination.
  • Mhembere D, Zheng D, Priebe CE, Vogelstein JT, Burns R (2017).  Knor: A NUMA-optimized in-memory, distributed and semi-external-memory k-means library.  HPDC 2017 - Proceedings of the 26th International Symposium on High-Performance Parallel and Distributed Computing.
  • Yoder J, Priebe C (2017).  Semi-supervised K-means++.  Journal of Statistical Computation and Simulation.  87(12).  2597-2608.
  • Tang M, Priebe C (2017).  Limit theorems for eigenvectors of the normalized Laplacian for random graphs.  Annals of Statistics.
  • Shen C, Vogelstein JT, Priebe CE (2017).  Manifold matching using shortest-path distance and joint neighborhood selection.  Pattern Recognition Letters.  92.
  • Cape J, Tang M, Priebe C (2017).  The two-to-infinity norm and singular subspace geometry with applications to high-dimensional statistics.
  • Rubin-Delanchy P, Priebe C, Tang M (2017).  Consistency of adjacency spectral embedding for the mixed membership stochastic blockmodel.
  • Priebe C, Park Y, Athreya A, Lyzinski V, Vogelstein J, Qin Y, Cocanougher B, Eichler K, Zlatic M, Cardona A (2017).  Semiparametric spectral modeling of the Drosophila connectome.
  • Zheng D, Mhembere D, Lyzinski V, Vogelstein JT, Priebe CE, Burns R (2017).  Semi-external memory sparse matrix multiplication for billion-node graphs.  IEEE Transactions on Parallel and Distributed Systems.  28(5).
  • Fishkind D, Adali S, Patsolic H, Meng L, Priebe C, Lyzinski V (2017).  Seeded graph matching.
  • Tang M, Athreya A, Sussman DL, Lyzinski V, Park Y, Priebe CE (2017).  A Semiparametric Two-Sample Hypothesis Testing Problem for Random Graphs.  Journal of Computational and Graphical Statistics.  26(2).
  • Shen C, Priebe C, Maggioni M, Vogelstein J (2017).  Joint embedding of graphs.
  • Maugis P-A. G, Priebe C, Olhede S.C, Wolfe P.J (2017).  Statistical inference for network samples using subgraph counts.
  • Lyzinski V, Tang M, Athreya A, Park Y, Priebe CE (2017).  Community Detection and Classification in Hierarchical Stochastic Blockmodels.  IEEE Transactions on Network Science and Engineering.  4(1).
  • Cape J, Tang M, Priebe CE (2017).  The kato-temple inequality and eigenvalue concentration with applications to graph inference.  Electronic Journal of Statistics.  11(2).
  • Lee NH, Tang R, Priebe CE, Rosen M (2016).  A Model Selection Approach for Clustering a Multinomial Sequence with Non-Negative Factorization.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  38(12).
  • Adali S, Priebe CE (2016).  Fidelity-Commensurability Tradeoff in Joint Embedding of Disparate Dissimilarities.  Journal of Classification.  33(3).
  • Priebe C, Adali S (2016).  Fidelity-Commensurability Tradeoff in Joint Embedding of Disparate Dissimilarities.  Journal of Classification.  33(3).  485-506.
  • Lyzinski V, Levin K, Fishkind DE, Priebe CE (2016).  On the consistency of the likelihood maximization vertex nomination scheme: Bridging the gap between maximum likelihood estimation and graph matching.  Journal of Machine Learning Research.  17.
  • Fishkind DE, Shen C, Park Y, Priebe CE (2016).  On the Incommensurability Phenomenon.  Journal of Classification.  (2).
  • Megarry WP, Cooney G, Comer DC, Priebe CE (2016).  Posterior probability modeling and image classification for archaeological site prospection: Building a survey efficacy model for identifying Neolithic felsite workshops in the Shetland Islands.  Remote Sensing.  8(6).
  • Priebe C, L. Chen , C. Shen , J. V. Vogelstein (2016).  Robust Vertex Classification.  38(3).  579-590.
  • Chen L, Shen C, Vogelstein JT, Priebe CE (2016).  Robust Vertex Classification.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  38(3).
  • Athreya A, Priebe CE, Tang M, Lyzinski V, Marchette DJ, Sussman DL (2016).  A Limit Theorem for Scaled Eigenvectors of Random Dot Product Graphs.  Sankhya A.  78(1).
  • Priebe C, Lee N, Tang R, Rosen M (2016).  A Model Selection Approach for Clustering a Multinomial Sequence with Non-Negative Factorization.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  38(12).  2345-2358.
  • Priebe C, Megarry W, Cooney C, D. C (2016).  Posterior Probability Modelling and Image Classification for Archaeological Site Prospection: Building a Survey Efficacy Model for Identifying Neolithic Felsite Workshops in the Shetland Islands.  Remote Sensing.  8(529).  1-18.
  • Lyzinski V, Fishkind DE, Fiori M, Vogelstein JT, Priebe CE, Sapiro G (2016).  Graph Matching: Relax at Your Own Risk.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  38(1).
  • Athreya A, Priebe CE, Tang M, Lyzinski V, Marchette DJ, Sussman DL (2016).  A limit theorem for scaled eigenvectors of random dot product graphs.  Sankhya: The Indian Journal of Statistics.  78A.
  • Suwan S, Lee DS, Tang R, Sussman DL, Tang M, Priebe CE (2016).  Empirical Bayes estimation for the stochastic blockmodel.  Electronic Journal of Statistics.  10(1).
  • Priebe C, Fishkind D, Shen C, Park Y (2016).  On the Incommensurability Phenomenon.  Journal of Classification.  33(2).  185-209.
  • Priebe C, Suwan S, Lee DS, Tang R, Sussman DL, Tang M (2016).  Empirical Bayes Estimation for the Stochastic Blockmodel.  Electronic Journal of Statistics.  10(1).  761-782.
  • Priebe C, Lyzinksi V, Levin K, Fishkind D (2016).  On the Consistency of the Likelihood Maximization Vertex Nomination Scheme: Bridging the Gap Between Likelihood Estimation and Graph Matching.  17(179).  1-34.
  • Priebe CE, Sussman DL, Tang M, Vogelstein JT (2015).  Statistical Inference on Errorfully Observed Graphs.  Journal of Computational and Graphical Statistics.  24(4).
  • Gray Roncal WR, Kleissas DM, Vogelstein JT, Manavalan P, Lillaney K, Pekala M, Burns R, Vogelstein RJ, Priebe CE, Chevillet MA, Hager GD (2015).  An automated images-to-graphs framework for high resolution connectomics.  Frontiers in Neuroinformatics.  9(AUGUST).
  • Priebe C, V. Lyzinski , D. L. Sussman , H. Pao , D. E. Fishkind , Y. Park , L. Chen , J. T. Vogelstein (2015).  Spectral Clustering for Divide-and-Conquer Graph Matching.  47.  70-87.
  • Kasthuri N, Hayworth KJ, Berger DR, Schalek RL, Conchello JA, Knowles-Barley S, Lee D, Vázquez-Reina A, Kaynig V, Jones TR, Roberts M, Morgan JL, Tapia JC, Seung HS, Roncal WG, Vogelstein JT, Burns R, Sussman DL, Priebe CE, Pfister H, Lichtman JW (2015).  Saturated Reconstruction of a Volume of Neocortex.  Cell.  162(3).
  • Priebe C, N. Kasthuri , K. J. Hayworth , D. R. Berger , R. L. Schalek , J. A. Conchello , S. Knowles-Barley , D. Lee , A. Vásquez-Réina , V. Kaynig , T. R. Jones , M. Roberts , J. L. Morgan , J. C. Tapia , H. S. Seung , W. G. Roncal , J. T. Vogelstein... (2015).  Saturated Reconstruction of a Volume of Neocortex.  162(3).  648-661.
  • Vogelstein JT, Priebe CE (2015).  Shuffled Graph Classification: Theory and Connectome Applications.  Journal of Classification.  32(1).
  • Vogelstein JT, Conroy JM, Lyzinski V, Podrazik LJ, Kratzer SG, Harley ET, Fishkind DE, Vogelstein RJ, Priebe CE (2015).  Fast Approximate Quadratic programming for graph matching.  PLoS ONE.  10(4).
  • Priebe C, S. Suwan , D. S. Lee (2015).  Bayesian Vertex Nomination Using Content and Context.  WIREs Computational Statistics.  7(6).  400-416.
  • Priebe C, M.A. Tang , A.S. Dietz , T. Yang , P.J. Pronovost (2015).  An Integrative Framework for Sensor-based Measurement of Teamwork in Healthcare.  22(1).  11-18.
  • Alkaya AF, Aksakalli V, Priebe C (2015).  A penalty search algorithm for the obstacle neutralization problem..  Computers & Operations Research.  53.  165-175.
  • Rosen MA, Dietz AS, Yang T, Priebe C, Pronovost PJ (2015).  An integrative framework for sensor-based measurement of teamwork in healthcare..  22(1).  11-18.
  • Marchette DJ, Choi SY, Rukhin A, Priebe CE (2015).  Neighborhood homogeneous labelings of graphs.  Journal of Combinatorial Mathematics and Combinatorial Computing.  93.
  • Rosen MA, Dietz AS, Yang T, Priebe CE, Pronovost PJ (2015).  An integrative framework for sensor-based measurement of teamwork in healthcare.  Journal of the American Medical Informatics Association : JAMIA.  22(1).
  • Lyzinski V, Fishkind DE, Priebe CE (2015).  Seeded graph matching for correlated Erdo″s-Rényi graphs.  Journal of Machine Learning Research.  15.
  • Priebe C, D. J. Marchette , S. Y. Choi , A. Rukhin (2015).  Neighborhood Homogeneous Labelings of Graphs.  93.  201-220.
  • Alkaya AF, Aksakalli V, Priebe CE (2015).  A penalty search algorithm for the obstacle neutralization problem.  Computers and Operations Research.  53.
  • Fishkind DE, Lyzinski V, Pao H, Chen L, Priebe CE (2015).  Vertex nomination schemes for membership prediction.  Annals of Applied Statistics.  9(3).
  • Priebe C, J. T. Vogelstein (2015).  Shuffled Graph Classification: Theory and Connectome of Graphs.  32.  3-20.
  • Priebe C, D. L. Sussman , M. Tang , J. T. Vogelstein (2015).  Statistical inference on errorfully observed graphs.  Journal of Computational and Graphical Statistics.  24(4).  930-953.
  • Suwan S, Lee DS, Priebe CE (2015).  Bayesian Vertex Nomination Using Content and Context.  Wiley Interdisciplinary Reviews: Computational Statistics.  7(6).
  • Priebe C, D. E. Fishkind , V. Lyzinski , H. Pao , L. Chen (2015).  Vertex Nomination Schemes for Membership Prediction.  Annals of Applied Statistics.  9(3).  1510-1532.
  • Lyzinski V, Sussman DL, Fishkind DE, Pao H, Chen L, Vogelstein JT, Park Y, Priebe CE (2014).  Spectral clustering for divide-and-conquer graph matching.  Parallel Computing.  47.
  • Vogelstein J, Park Y, Ohyama T, Kerr RA, Truman JW, Priebe C, Zlatic M (2014).  Discovery of brainwide neural-behavioral maps via multiscale unsupervised structure learning..  Science.  344(6182).  386-392.
  • Wang H, Tang M, Park Y, Priebe C (2014).  Locality Statistics for Anomaly Detection in Time Series of Graphs.  Ieee Transactions on Signal Processing.  62(3).  703-717.
  • Wang H, Tang M, Park Y, Priebe CE (2014).  Locality statistics for anomaly detection in time series of graphs.  IEEE Transactions on Signal Processing.  62(3).
  • Sussman DL, Tang M, Priebe CE (2014).  Consistent latent position estimation and vertex classification for random dot product graphs.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  36(1).
  • Sussman DL, Tang M, Priebe C (2014).  Consistent Latent Position Estimation and Vertex Classification for Random Dot Product Graphs.  IEEE transactions on pattern analysis and machine intelligence.  36(1).  48-57.
  • D.L.Sussman , M.Tang , Priebe C (2014).  Consistent latent position estimation and vertex clasifcation for random dot product graphs.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  36.  48-57.
  • Shen C, Sun M, Tang M, Priebe C (2014).  Generalized canonical correlation analysis for classification..  J. Multivariate Analysis ().  130.  310-322.
  • C.Shen , M.Sun , M.Tang , Priebe C (2014).  Generalized canonical correlation analysis for classification in high dimensions.  Journal of Multivariate Analysis.  130.  310-322.
  • H.Wang , M.Tang , Park Y, Priebe C (2014).  Locality statistics for anomaly detection in time-series of graphs.  IEEE Transactions on Signal Processing.  62.  703-717.
  • Priebe CE, Lyzinski V, Sussman D, Athreya A, Tang M (2014).  Perfect Clustering for Stochastic Blockmodel Graphs via Adjacency Spectral Embedding.  Electronic Journal of Statistics.  8(2).  2905-2922.
  • Priebe C, Fishkind D, Lyzinski V (2014).  Seeded graph matching for correlated Erdos-Renyi graphs.  Journal of Machine Learning Research.  15(Nov).  3513-3540.
  • Vogelstein JT, Park Y, Ohyama T, Kerr RA, Truman JW, Priebe CE, Zlatic M (2014).  Discovery of brainwide neural-behavioral maps via multiscale unsupervised structure learning.  Science.  344(6182).
  • Lyzinski V, Sussman DL, Tang M, Athreya A, Priebe CE (2014).  Perfect clustering for stochastic blockmodel graphs via adjacency spectral embedding.  Electronic Journal of Statistics.  8.
  • V.Lyzinski , D.L.Sussman , M.Tang , Athreya D, Priebe C (2014).  Perfect clustering for stochastic blockmodel graphs via adjacency spectral embedding.  Electronic Journal of Statistics.  8.  2905-2922.
  • Shen C, Sun M, Tang M, Priebe CE (2014).  Generalized canonical correlation analysis for classification.  Journal of Multivariate Analysis.  130.
  • Priebe C, D.L.Sussman , M.Tang , Vogelstein J (2014).  Statistical inference on errorfully observed graphs.  Journal of Computational and Graphical Statistics.
  • Qin Y, Priebe CE (2013).  Maximum Lq-likelihood estimation via the expectation-maximization algorithm: A robust estimation of mixture models.  Journal of the American Statistical Association.  108(503).
  • Mhembere D, Gray Roncal W, Sussman D, Priebe CE, Jung R, Ryman S, Vogelstein RJ, Vogelstein JT, Burns R (2013).  Computing scalable multivariate glocal invariants of large (brain-) graphs.  2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings.
  • Wang H, Tang M, Priebe C, Park Y (2013).  Inference in time series of graphs using locality statistics.  2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings.
  • Lee NH, Minh J, Tang M, Priebe CE (2013).  On latent position inference from doubly stochastic messaging activities.  Multiscale Modeling and Simulation.  11(3).
  • Priebe CE, Vogelstein J, Bock D (2013).  Optimizing the quantity/quality trade-off in connectome inference.  Communications in Statistics - Theory and Methods.  42(19).
  • Qin Y, Priebe C (2013).  Maximum Lq-Likelihood Estimation via the Expectation-Maximization Algorithm: A Robust Estimation of Mixture Models.  Journal of the American Statistical Association.  108(503).  914-928.
  • Priebe C, Marchette DJ, Ma Z, Adali S (2013).  Manifold matching: Joint optimization of fidelity and commensurability.  Brazilian Journal of Probability and Statistics.  27(3).  377-400.
  • Vogelstein J, Gray WR, Vogelstein RJ, Priebe C (2013).  Graph Classification using Signal Subgraphs: Applications in Statistical Connectomics.  IEEE transactions on pattern analysis and machine intelligence.  35(7).  1539-1551.
  • Priebe CE, Marchette DJ, Ma Z, Adali S (2013).  Manifold matching: Joint optimization of fidelity and commensurability.  Brazilian Journal of Probability and Statistics.  27(3).
  • Tang M, Sussman DL, Priebe C (2013).  Universally Consistent Vertex Classification for Latent Positions Graphs.  Annals of Statistics.  41(3).  1406-1430.
  • Vogelstein JT, Roncal WG, Jacob Vogelstein R, Priebe CE (2013).  Graph classification using signal-subgraphs: Applications in statistical connectomics.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  35(7).
  • Sun M, Priebe CE (2013).  Efficiency investigation of manifold matching for text document classification.  Pattern Recognition Letters.  34(11).
  • Lee N, Tang M, Yoder J, Priebe C (2013).  On latent position inference from doubly stochastic messaging activities.  Multiscale Modeling & Simulation.  11(3).  683-718.
  • Athreya A, Lyzinski V, Marchette DJ, Priebe C, Sussman DL, Tang M (2013).  A central limit theorem for scaled eigenvectors of random dot product graphs.  arXiv.org.
  • Tang M, Park Y, Lee N, Priebe C (2013).  Attribute fusion in a latent process model for timeseries of graphs.  IEEE Transactions on Signal Processing.  61(7).  1721-1732.
  • Lyzinski V, Fishkind D, Priebe C (2013).  Seeded graph matching for correlated Erdos-Rényi graphs.  arXiv.org.
  • Tang M, Park Y, Lee NH, Priebe CE (2013).  Attribute fusion in a latent process model for time series of graphs.  IEEE Transactions on Signal Processing.  61(7).
  • Park Y, Priebe C, Youssef A (2013).  Anomaly Detection in Time Series of Graphs using Fusion of Graph Invariants.  IEEE Journal of Selected Topics in Signal Processing.  7(1).  67-75.
  • Park Y, Priebe CE, Youssef A (2013).  Anomaly detection in time series of graphs using fusion of graph invariants.  IEEE Journal on Selected Topics in Signal Processing.  7(1).
  • Sun M, Priebe CE, Tang M (2013).  Generalized canonical correlation analysis for disparate data fusion.  Pattern Recognition Letters.  34(2).
  • Lee N, J.Yoder , M.Tang , Priebe C (2013).  On latent position inference from doubly stochastic messaging activities.  Multiscale Modeling and Simulation.  11.  683-718.
  • M.Tang , Park Y, Lee N, Priebe C (2013).  Attribute fusion in a latent process model for time series of graphs.  IEEE Transactions in Signal Processing.  61.  1721-1732.
  • Fishkind D, D.L.Sussman , M.Tang , Vogelstein J, Priebe C (2013).  Consistent adjacency-spectral partitioning for the stochastic block model when the model parameters are unknown.  Siam Journal on Matrix Analysis and Applications.  34.  23-39.
  • Priebe C, Vogelstein J, Bock D (2013).  Optimizing the Quantity/Quality Trade-Off in Connectome Inference.  Communications in Statistics-Theory and Methods.  42(19).  3455-3462.
  • M.Tang , D.L.Sussman , Priebe C (2013).  Universally consistent vertex classification for latent positions graphs.  Annals of Statistics..  31.  1406-1430.
  • Feng J, Tang X, Tang M, Priebe C, Miller M (2013).  Metric space structures for computational anatomy.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  8184 LNCS.
  • M.Sun , Priebe C, M.Tang (2013).  Generalized canonical correlation analysis for disparate data fusion.  Pattern Recognition Letters.  34.  194-200.
  • Sun M, Priebe C (2013).  Efficiency investigation of manifold matching for text document classification.  Pattern Recognition Letters.  34(11).  1263-1269.
  • Sun M, Priebe C, Tang M (2013).  Generalized Canonical Correlation Analysis for Disparate Data Fusion.  Pattern Recognition Letters.  194-200.
  • Sussman DL, Tang M, Fishkind DE, Priebe CE (2012).  A consistent adjacency spectral embedding for stochastic blockmodel graphs.  Journal of the American Statistical Association.  107(499).
  • Sun M, Tang M, Priebe CE (2012).  A comparison of graph embedding methods for vertex nomination.  Proceedings - 2012 11th International Conference on Machine Learning and Applications, ICMLA 2012.  1.
  • Fishkind DE, Sussman DL, Tang M, Vogelstein JT, Priebe CE (2012).  Consistent adjacency-spectral partitioning for the stochastic block model when the model parameters are unknown.  SIAM Journal on Matrix Analysis and Applications.  34(1).
  • Sussman DL, Tang M, Fishkind D, Priebe C (2012).  A consistent adjacency spectral embedding for stochastic blockmodel graphs.  Journal of the American Statistical Association.  1119-1128.
  • Hawes CM, Priebe CE (2012).  A bootstrap interval estimator for Bayes' classification error.  2012 IEEE Statistical Signal Processing Workshop, SSP 2012.
  • Priebe CE, Solka JL, Marchette DJ, Bryant AC (2012).  Quantitative Horizon Scanning for Mitigating Technological Surprise: Detecting the Potential for Collaboration at the Interface.  Statistical Analysis and Data Mining.  5(3).
  • Ma Z, Marchette DJ, Priebe CE (2012).  Fusion and inference from multiple data sources in a commensurate space.  Statistical Analysis and Data Mining.  5(3).
  • Rukhin A, Priebe CE (2012).  On the limiting distribution of a graph scan statistic.  Communications in Statistics - Theory and Methods.  41(7).
  • Rukhin A, Priebe C (2012).  On the limiting distribution of a graph scan statistic.  Communications in Statistics - Theory and Methods.  41(7).  1151-1170.
  • Priebe C, Solka JL, Marchette DJ (2012).  Quantitative Horizon Scanning for Mitigating Technological Surprise: Detecting the potential for collaboration at the interface.  Statistical Analysis and Data Mining.  5.  178-186.
  • Ma Z, Marchette DJ, Priebe C (2012).  Fusion and inference from multiple data sources in a commensurate space.  Statistical Analysis and Data Mining.  5(3).  187-193.
  • Tilton JC, Comer DC, Priebe CE, Sussman D, Chen L (2012).  Refinement of a method for identifying probable archaeological sites from remotely sensed data.  Proceedings of SPIE - The International Society for Optical Engineering.  8390.
  • Fishkind D, Sussman DL, Tang M, Vogelstein J, Priebe C (2012).  Consistent adjacency-spectral partitioning for the stochastic block model when the model parameters are unknown.  SIAM Journal on Matrix Analysis and Applicationsins.  stat.ME.
  • Vogelstein JT, Vogelstein RJ, Priebe CE (2011).  Are mental properties supervenient on brain properties?.  Scientific Reports.  1.
  • Priebe CE (2011).  Fisher's conditionality principle in statistical pattern recognition.  American Statistician.  65(3).
  • Lee NH, Priebe CE (2011).  A latent process model for time series of attributed random graphs.  Statistical Inference for Stochastic Processes.  14(3).
  • Yang T, Priebe C (2011).  The Effect of Model Misspecification on Semi-Supervised Classification.  IEEE transactions on pattern analysis and machine intelligence.  33(10).  2093-2103.
  • Priebe CE, Lee NH, Park Y, Tang M (2011).  Attribute fusion in a latent process model for time series of graphs.  IEEE Workshop on Statistical Signal Processing Proceedings.
  • Yang T, Priebe CE (2011).  The effect of model misspecification on semi-supervised classification.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  33(10).
  • Borges N, Coppersmith GA, Meyer GGL, Priebe CE (2011).  Anomaly detection for random graphs using distributions of vertex invariants.  2011 45th Annual Conference on Information Sciences and Systems, CISS 2011.
  • Aksakalli V, Fishkind D, Priebe C, Ye X (2011).  The Reset Disambiguation Policy for Navigating Stochastic Obstacle Fields.  Naval Research Logistics.  58(4).  389-399.
  • Aksakalli V, Fishkind DE, Priebe CE, Ye X (2011).  The reset disambiguation policy for navigating stochastic obstacle fields.  Naval Research Logistics.  58(4).
  • Pao H, Coppersmith GA, Priebe CE (2011).  Statistical inference on random graphs: Comparative power analyses via Monte Carlo.  Journal of Computational and Graphical Statistics.  20(2).
  • Mohan NR, Priebe C, Par Y, John M (2011).  Statistical analysis of hippocampus shape using a modified Mann-Whitney-Wilcoxon test.  International Journal of Bio-Science and Bio-Technology.  3(1).
  • Rukhin A, Priebe C (2011).  A comparative power analysis of the maximum degree and size invariants for random graph inference.  Journal of Statistical Planning and Inference.  141(2).  1041-1046.
  • Ye X, Fishkind DE, Abrams L, Priebe CE (2011).  Sensor information monotonicity in disambiguation protocols.  Journal of the Operational Research Society.  62(1).
  • Vogelstein J, Vogelstein RJ, Priebe C (2011).  Are mental properties supervenient on brain properties?.  Scientific Reports.  1.
  • Pao H, Coppersmith GA, Priebe C (2011).  Statistical inference on random graphs: Comparative power analyses via Monte Carlo.  Journal of Computational and Graphical Statistics.
  • Ye X, Fishkind D, Abrams L, Priebe C (2011).  Sensor information monotonicity in disambiguation protocols.  Journal of the Operational Research Society.  62(1).  142-151.
  • Lee N, Priebe C (2011).  A latent process model for time series of attributed random graphs.  Statistical inference for stochastic processes.  14(3).  231-253.
  • Priebe C (2011).  Fisher's conditionality principle in statistical pattern recognition.  The American Statistician.  65(3).  167-169.
  • Gorin AL, Priebe CE, Grothendieck J (2010).  Random attributed graphs for statistical inference from content and context.  ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings.
  • Ma Z, Cardinal-Stakenas A, Park Y, Trosset MW, Priebe C (2010).  Dimensionality Reduction on the Cartesian Product of Embeddings of Multiple Dissimilarity Matrices.  Journal of Classification.  27(3).  307-321.
  • Ma Z, Cardinal-Stakenas A, Park Y, Trosset MW, Priebe CE (2010).  Dimensionality reduction on the Cartesian product of embeddings of multiple dissimilarity matrices.  Journal of Classification.  27(3).
  • Rukhin A, Priebe CE (2010).  A comparative power analysis of the maximum degree and size invariants for random graph inference.  Journal of Statistical Planning and Inference.  (2).
  • Blatz J, Fishkind DE, Priebe CE (2010).  Efficient, optimal stochastic-action selection when limited by an action budget.  Mathematical Methods of Operations Research.  72(1).
  • Blatz J, Fishkind D, Priebe C (2010).  Efficient, optimal stochastic-action selection when limited by an action budget.  Mathematical Methods of Operations Research.  72(1).  63-74.
  • Grothendieck J, Priebe CE, Gorin AL (2010).  Statistical inference on attributed random graphs: Fusion of graph features and content.  Computational Statistics and Data Analysis.  54(7).
  • Priebe CE, Park Y, Marchette DJ, Conroy JM, Grothendieck J, Gorin AL (2010).  Statistical inference on attributed random graphs: Fusion of graph features and content: An experiment on time series of Enron graphs.  Computational Statistics and Data Analysis.  54(7).
  • Vogelstein RJ, Harshbarger SD, McLoughlin MP, Beaty JD, Yantis S, Connor CE, Thakor NV, Priebe C, Etienne-Cummings R (2010).  Research program in applied neuroscience.  Johns Hopkins APL Technical Digest (Applied Physics Laboratory).  28(3).
  • Carliles S, Budavari T, Heinis S, Priebe C, Szalay S (2010).  Random Forests for Photometric Redshifts.  The Astrophysical Journal.  712.  511-515.
  • Carliles S, Budavári T, Heinis S, Priebe C, Szalay AS (2010).  Random forests for photometric redshifts.  Astrophysical Journal.  712(1).
  • Priebe C, Park Y, Marchette DJ, Conroy JM (2010).  Statistical inference on attributed random graphs: Fusion of graph features and content: An experiment on time series of Enron graphs.  Computational Statistics and Data Analysis.  54.  1766-1776.
  • Grothendieck J, Priebe C, Gorin, A L (2010).  Statistical inference on attributed random graphs: Fusion of graph features and content.  Computational Statistics and Data Analysis.  54.  1777-1790.
  • Vogelstein J, Harshbarger S, McLoughlin M, Beaty J, Yantis S, Connor C, Thakor N, Priebe C, Etienne-Cummings R (2010).  Research Program in Applied Neuroscience.  Johns Hopkins APL technical digest.  28(3).  222-223.
  • Ye X, Priebe C (2010).  A Graph-Search Based Navigation Algorithm for Traversing A Potentially Hazardous Area with Disambiguation..  IJORIS.  1(3).  14-27.
  • Park Y, Priebe CE, Marchette DJ, Youssef A (2009).  Anomaly detection using scan statistics on time series hypergraphs.  Society for Industrial and Applied Mathematics - 9th SIAM International Conference on Data Mining 2009, Proceedings in Applied Mathematics.  3.
  • Mohan NR, Priebe C, Park Y, John M (2009).  Statistical analysis of hippocampus shape using a modified Mann-Whitney-Wilcoxon test.  Communications in Computer and Information Science.  57 CCIS.
  • Miller M, Priebe C, Qiu A, Fischl B, Kolasny A, Brown T, Park Y, Ratnanather J, Busa E, Jovicich J, Yu P, Dickerson BC, Buckner RL, BIRN M (2009).  Collaborative computational anatomy: an MRI morphometry study of the human brain via diffeomorphic metric mapping..  Human brain mapping.  30(7).  2132-2141.
  • Miller MI, Priebe CE, Qiu A, Fischl B, Kolasny A, Brown T, Park Y, Ratnanather JT, Busa E, Jovicich J, Yu P, Dickerson BC, Buckner RL (2009).  Collaborative computational anatomy: An MRI morphometry study of the human brain via diffeomorphic metric mapping.  Human Brain Mapping.  30(7).
  • Rukhin A, Priebe CE, Healy DM (2009).  On the monotone likelihood ratio property for the convolution of independent binomial random variables.  Discrete Applied Mathematics.  157(11).
  • Mohan NR, Priebe C, Park Y, John M (2009).  Statistical Analysis of Hippocampus Shape Using a Modified Mann-Whitney-Wilcoxon Test..  FGIT-BSBT.  57(Chapter 7).  45-52.
  • Rukhin A, Priebe C, Healy, Dennis M Jr (2009).  On the monotone likelihood ratio property for the convolution of independent binomial random variables.  Discrete Applied Mathematics.  157(11).  2562-2564.
  • Lee NA, Priebe CE, Miller MI, Ratnanather JT (2008).  Validation of alternating Kernel mixture method: application to tissue segmentation of cortical and subcortical structures..  Journal of biomedicine & biotechnology.  2008.
  • Giles KE, Trosset MW, Marchette DJ, Priebe C (2008).  Iterative denoising.  Computational Statistics.  23(4).  497-517.
  • Giles KE, Trosset MW, Marchette DJ, Priebe CE (2008).  Iterative denoising.  Computational Statistics.  23(4).
  • Karakos D, Khudanpur S, Priebe CE (2008).  Computation of Csiszár's mutual information of order α.  IEEE International Symposium on Information Theory - Proceedings.
  • Trosset MW, Priebe CE, Park Y, Miller MI (2008).  Semisupervised learning from dissimilarity data.  Computational Statistics and Data Analysis.  52(10).
  • Trosset MW, Priebe CE (2008).  The out-of-sample problem for classical multidimensional scaling.  Computational Statistics and Data Analysis.  52(10).
  • Karakos D, Khudanpur S, Marchette DJ, Papamarcou A, Priebe CE (2008).  On the minimization of concave information functionals for unsupervised classification via decision trees.  Statistics and Probability Letters.  78(8).
  • Priebe CE, Wallis WD (2008).  On the anomalous behaviour of a class of locality statistics.  Discrete Mathematics.  308(10).
  • Park Y, Priebe CE, Miller MI, Mohan NR, Botteron KN (2008).  Statistical analysis of twin populations using dissimilarity measurements in hippocampus shape space.  Journal of Biomedicine and Biotechnology.  2008(1).
  • Priebe C, Wallis W (2008).  On the anomalous behaviour of a class of locality statistics.  Discrete Mathematics.
  • Trosset M, Priebe C (2008).  The out-of-sample problem for classical multidimensional scaling.  Computational Statistics and Data Analysis.
  • Trosset MW, Priebe C, Park Y, Miller M (2008).  Semisupervised learning from dissimilarity data..  Computational Statistics and Data Analysis.  52(10).  4643-4657.
  • Park Y, Priebe C, Miller M, Mohan NR, Botteron KN (2008).  Statistical analysis of twin populations using dissimilarity measurements in hippocampus shape space.  Journal of biomedicine & biotechnology.  2008(1).  -5.
  • Marchette DJ, Priebe C (2008).  Predicting unobserved links in incompletely observed networks.  Computational Statistics and Data Analysis.  52(3).  1373-1386.
  • Marchette DJ, Priebe C (2008).  Scan statistics for interstate alliance graphs.  Connections.  2.  43-64.
  • Karakos D, Khudanpur S, Marchette DJ, Papamarcou A, Priebe C (2008).  On the minimization of concave information functionals for unsupervised classification via decision trees.  Statistics & Probability Letters.  78(8).  975-984.
  • LEE NA, Priebe C, Miller M, Ratnanather J (2008).  Validation of alternating Kernel mixture method: Application to tissue segmentation of cortical and subcortical structures.  Journal of Biomedicine & Biotechnology.  Article No.: 346129.
  • Marchette DJ, Priebe CE (2008).  Predicting unobserved links in incompletely observed networks.  Computational Statistics and Data Analysis.  52(3).
  • Lee NA, Priebe CE, Ratnanather JT, Miller MI (2007).  Validation of alternating kernel mixture method based segmentation of the human brain.  Proceedings of the Frontiers in the Convergence of Bioscience and Information Technologies, FBIT 2007.
  • Karakos D, Eisner J, Khudanpur S, Priebe CE (2007).  Cross-instance tuning of unsupervised document clustering algorithms.  NAACL HLT 2007 - Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics, Proceedings of the Main Conference.
  • Priebe CE, Park Y, Miller MI, Mohan NR, Botteron KN (2007).  Hippocampus shape-space analysis of clinically depressed, high risk, and control populations.  Proceedings of the Frontiers in the Convergence of Bioscience and Information Technologies, FBIT 2007.
  • Fishkind D, Priebe C, Giles KE, Smith LN, Aksakalli V (2007).  Disambiguation protocols based on risk simulation.  Ieee Transactions on Systems Man and Cybernetics Part a-Systems and Humans.  37(5).  814-823.
  • Fishkind DE, Priebe CE, Giles KE, Smith LN, Aksakalli V (2007).  Disambiguation protocols based on risk simulation.  IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans.  37(5).
  • Karakos D, Khudanpur S, Eisner J, Priebe CE (2007).  Iterative denoising using Jensen-Renyi divergences with an application to unsupervised document categorization.  ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings.  2.
  • John M, Priebe CE (2007).  A data-adaptive methodology for finding an optimal weighted generalized Mann-Whitney-Wilcoxon statistic.  Computational Statistics and Data Analysis.  51(9).
  • Ceyhan E, Priebe C, Marchette DJ (2007).  A new family of random graphs for testing spatial segregation.  Canadian Journal of Statistics-Revue Canadienne De Statistique.  35(1).  27-50.
  • Ceyhan E, Priebe CE, Marchette DJ (2007).  A new family of random graphs for testing spatial segregation.  Canadian Journal of Statistics.  35(1).
  • John M, Priebe C (2007).  A data-adaptive methodology for finding an optimal weighted generalized Mann-Whitney-Wilcoxon statistic.  Computational Statistics and Data Analysis.  51(9).  4337-4353.
  • DeVinney J, Priebe CE (2006).  A new family of proximity graphs: Class cover catch digraphs.  Discrete Applied Mathematics.  154(14).
  • Priebe C, Marchette DJ, Park Y, Muise RR (2006).  Application of integrated sensing and processing decision trees for target detection and localization on digital mirror array imagery.  Applied optics.  45(13).  3022-3030.
  • Priebe CE, Marchette DJ, Park Y, Mulse RR (2006).  Application of integrated sensing and processing decision trees for target detection and localization on digital mirror array imagery.  Applied Optics.  45(13).
  • Ceyhan E, Priebe CE, Wierman JC (2006).  Relative density of the random r-factor proximity catch digraph for testing spatial patterns of segregation and association.  Computational Statistics and Data Analysis.  50(8).
  • Priebe CE, Miller MI, Tilak Ratnanather J (2006).  Segmenting magnetic resonance images via hierarchical mixture modelling.  Computational Statistics and Data Analysis.  50(2).
  • Priebe C, Miller M, Ratnanather J (2006).  Segmenting magnetic resonance images via hierarchical mixture modelling.  Computational Statistics and Data Analysis.  50(2).  551-567.
  • Ceyhan E, Priebe C, Wierman J (2006).  Relative density of the random r-factor proximity catch digraph for testing spatial patterns of segregation and association.  Computational Statistics and Data Analysis.  50(8).  1925-1964.
  • DeVinney J, Priebe C (2006).  A new family of proximity graphs: Class cover catch digraphs..  Discrete Applied Mathematics.  154(14).  1975-1982.
  • Ceyhan E, Priebe C (2006).  On the distribution of the domination number of a new family of parametrized random digraphs..  MASA.  1(4).  231-255.
  • Jovicich J, Beg MF, Pieper S, Priebe C, Miller MM, Buckner R, Rosen B (2005).  Biomedical informatics research network: Integrating multi-site neuroimaging data acquisition, data sharing and brain morphometric processing.  Proceedings - IEEE Symposium on Computer-Based Medical Systems.
  • Priebe CE, Conroy JM, Marchette DJ, Park Y (2005).  Scan statistics on enron graphs.  Computational and Mathematical Organization Theory.  11(3).
  • Eveland CK, Socolinsky DA, Priebe CE, Marchette DJ (2005).  A hierarchical methodology for class detection problems with skewed priors.  Journal of Classification.  22(1).
  • Ceyhan E, Priebe CE (2005).  The use of domination number of a random proximity catch digraph for testing spatial patterns of segregation and association.  Statistics and Probability Letters.  73(1).
  • Priebe CE, Fishkind DE, Abrams L, Piatko CD (2005).  Random disambiguation paths for traversing a mapped hazard field.  Naval Research Logistics.  52(3).
  • Priebe C, Fishkind D, Abrams L, Piatko CD (2005).  Random disambiguation paths for traversing a mapped hazard field.  Naval Research Logistics.  52(3).  285-292.
  • Karakos D, Khudanpur S, Eisner J, Priebe CE (2005).  Unsupervised classification via decision trees: An information-theoretic perspective.  ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings.  V.
  • Eveland CK, Socolinsky DA, Priebe C, Marchette DJ (2005).  A hierarchical methodology for class detection problems with skewed priors.  Journal of Classification.  22(1).  17-48.
  • Ceyhan E, Priebe C (2005).  The use of domination number of a random proximity catch digraph for testing spatial patterns of segregation and association.  Statistics & Probability Letters.  73(1).  37-50.
  • Priebe C, Conroy JM, Marchette DJ, Park Y (2005).  Scan statistics on enron graphs.  Computational and Mathematical Organization Theory.  3.  229-247.
  • Marchette DJ, Wegman EJ, Priebe CE (2004).  Fast Algorithms for Classification Using Class Cover Catch Digraphs.  Handbook of Statistics.  24.
  • Johannsen DA, Wegman EJ, Solka JL, Priebe C (2004).  Simultaneous selection of features and metric for optimal nearest neighbor classification.  Communications in Statistics-Theory and Methods.  33(9).  2137-2157.
  • Johannsen DA, Wegman EJ, Solka JL, Priebe CE (2004).  Simultaneous selection of features and metric for optimal nearest neighbor classification.  Communications in Statistics - Theory and Methods.  33(9 SPEC.ISS.).
  • Priebe CE, Marchette DJ, Healy DM (2004).  Integrated sensing and processing decision trees.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  26(6).
  • Priebe C, Marchette DJ, Healy DM (2004).  Integrated sensing and processing decision trees..  IEEE transactions on pattern analysis and machine intelligence.  26(6).  699-708.
  • Abrams L, Fishkind D, Priebe C (2004).  The generalized spherical homeomorphism theorem for digital images..  IEEE transactions on medical imaging.  23(5).  655-657.
  • Abrams L, Fishkind DE, Priebe CE (2004).  The generalized spherical homeomorphism theorem for digital images.  IEEE Transactions on Medical Imaging.  23(5).
  • Beg MF, Ceritoglu C, Kolasny AE, Priebe C, Ratnanather J, Yashinski R, Younes L, Yu P, Jovicich J, Buckner RL, others (2004).  Biomedical Informatics Research Network: Multi-Site Processing Pipeline for Shape Analysis of Brain Structures.  Human Brain Mapping, 10th Annual Meeting; Budapest, Hungary.
  • Miller MI, Hosakere M, Barker AR, Priebe CE, Lee N, Ratnanather JT, Wang L, Gado M, Morris JC, Csernansky JG (2003).  Labeled cortical mantle distance maps of the cingulate quantify differences between dementia of the Alzheimer type and healthy aging.  Proceedings of the National Academy of Sciences of the United States of America.  100(25).
  • Miller M, Hosakere M, Barker, A R , Priebe C, Lee N, Ratnanather J, Wang L, Gado M, Morris JC, Csernansky JG (2003).  Labeled Cortical Mantle Distance Maps of the Cingulate Quantify Differences between Dementia of the Alzheimer Type and Healthy Aging.  Proceedings of the National Academy of Sciences of the United States of America.  100(25).  15172-15177.
  • Ratnanather JT, Priebe CE, Miller MI (2003).  Semi-automated segmentation of cortical subvolumes via hierarchical mixture modelling.  Proceedings of SPIE - The International Society for Optical Engineering.  5032 III.
  • Priebe CE, Solka JL, Marchette DJ, Clark BT (2003).  Class cover catch digraphs for latent class discovery in gene expression monitoring by DNA microarrays.  Computational Statistics and Data Analysis.  43(4).
  • Priebe CE, Marchette DJ, DeVinney JG, Socolinsky DA (2003).  Classification using class cover catch digraphs.  Journal of Classification.  20(1).
  • Pilla R, Tao P, Priebe C (2003).  Adaptive Methods for Spatial Scan Analysis via Semiparametric Mixture Models.  Journal of Computational and Graphical Statistics.  12(2).  332-353.
  • Pilla RS, Tao PP, Priebe CE (2003).  Adaptive methods for spatial scan analysis via semiparametric mixture models.  Journal of Computational and Graphical Statistics.  12(2).
  • Olson T, Pang JS, Priebe C (2003).  A likelihood-MPEC approach to target classification.  Mathematical Programming.  96(1).  1-31.
  • Olson T, Pang JS, Priebe C (2003).  A likelihood-MPEC approach to target classification.  Mathematical Programming, Series B.  96(1).
  • Marchette DJ, Priebe CE (2003).  Characterizing the scale dimension of a high-dimensional classification problem.  Pattern Recognition.  36(1).
  • Priebe C, Marchette DJ, DeVinney JG, Socolinsky DA (2003).  Classification using class cover catch digraphs.  Journal of Classification.  20(1).  3-23.
  • Marchette DJ, Priebe C (2003).  Characterizing the scale dimension of a high-dimensional classification problem.  Pattern Recognition.  36(1).  45-60.
  • Priebe C, Solka JL, Marchette DJ, Clark BT (2003).  Class cover catch digraphs for latent class discovery in gene expression monitoring by DNA microarrays.  Computational Statistics and Data Analysis.  43(4).  621-632.
  • Abrams L, Fishkind D, Priebe C (2002).  A proof of the spherical homeomorphism conjecture for surfaces.  IEEE transactions on medical imaging.  21(12).  1564-1566.
  • James F, Priebe C, Marchette DJ (2002).  Consistent Estimation Of Mixture Complexity.
  • Xie J, Priebe CE (2002).  A weighted generalization of the Mann-Whitney-Wilcoxon statistics.  Journal of Statistical Planning and Inference.  102(2).
  • Xie JD, Priebe C (2002).  A weighted generalization of the Mann-Whitney-Wilcoxon statistic.  Journal of Statistical Planning and Inference.  102(2).  441-466.
  • Solka JL, Priebe C, Clark BT (2002).  A Visualization Framework for the Analysis of Hyperdimensional Data..  Int. J. Image Graphics ().  2(1).  145-161.
  • Naiman DQ, Priebe CE (2001).  Computing scan statistic p values using importance sampling, with applications to genetics and medical image analysis.  Journal of Computational and Graphical Statistics.  10(2).
  • Priebe CE, Devinney JG, Marchette DJ (2001).  On the distribution of the domination number for random class cover catch digraphs.  Statistics and Probability Letters.  55(3).
  • Piatko CD, Priebe C, Cowen L, Wang IJ, McNamee P (2001).  Path planning for mine countermeasures command and control.  Proceedings of SPIE - The International Society for Optical Engineering.  4394(2).
  • James LF, Priebe CE, Marchette DJ (2001).  Consistent estimation of mixture complexity.  Annals of Statistics.  29(5).
  • Naiman D, Priebe C (2001).  Computing Scan Statistic p Values Using Importance Sampling, with Applications to Genetics and Medical Image Analysis.  Journal of Computational and Graphical Statistics.  10(2).  296-328.
  • Priebe CE (2001).  Olfactory classification via interpoint distance analysis.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  23(4).
  • Priebe CE, Naiman DQ, Cope LM (2001).  Importance sampling for spatial scan analysis: Computing scan statistic p-values for marked point processes.  Computational Statistics and Data Analysis.  35(4).
  • Priebe CE, Chen D (2001).  Spatial scan density estimates.  Technometrics.  43(1).
  • Priebe C, Naiman D, Cope LM (2001).  Importance sampling for spatial scan analysis: computing scan statistic p-values for marked point processes.  Computational Statistics and Data Analysis.  35(4).  475-485.
  • Priebe C, DeVinney JG, Marchette DJ (2001).  On the distribution of the domination number for random class cover catch digraphs.  Statistics & Probability Letters.  55(3).  239-246.
  • Priebe C (2001).  Olfactory Classification via Interpoint Distance Analysis..  IEEE transactions on pattern analysis and machine intelligence.  23(4).  404-413.
  • Xie J, Priebe CE (2000).  Generalizing the mann-whitney-wilcoxon statistic.  Journal of Nonparametric Statistics.  12(5).
  • Lee D, Priebe C (2000).  Exact mean and mean squared error of the smoothed bootstrap mean integrated squared error estimator.  Computational Statistics.  15(2).
  • Priebe CE, Marchette DJ (2000).  Alternating kernel and mixture density estimates.  Computational Statistics and Data Analysis.  35(1).
  • Priebe C, Marchette DJ (2000).  Alternating kernel and mixture density estimates.  Computational Statistics and Data Analysis.  35(1).  43-65.
  • Xie JD, Priebe C (2000).  Generalizing the Mann-Whitney-Wilcoxon statistic.  Journal of Nonparametric Statistics.  12(5).  661-682.
  • Marchette DJ, Priebe CE (2000).  ANDRomeda: Adaptive nonlinear dimensionality reduction.  Proceedings of SPIE - The International Society for Optical Engineering.  4055.
  • John M, Priebe CE (2000).  A data-adaptive methodology for finding an optimal weighted generalized Mann�Whitney�Wilcoxon statistic.  Journal of Nonparametric Statistics.  12(5).
  • Lee D, Priebe C (2000).  Exact mean and mean squared error of the smoothed bootstrap mean integrated squared error estimator.  Computational Statistics.  15(2).  169-181.
  • Priebe CE, Cowen LJ (1999).  A generalized Wilcoxon-Mann-Whitney statistic.  Communications in Statistics - Theory and Methods.  28(12).
  • Friedman HS, Priebe CE (1999).  Smoothing bandwidth selection for response latency estimation.  Journal of Neuroscience Methods.  87(1).
  • Cowen LJ, Priebe C (1999).  A generalized Wilcoxon-Mann-Whitney statistic.  Communications in Statistics-Theory and Methods.  28(12).  2871-2878.
  • Friedman HS, Priebe C (1999).  Smoothing bandwidth selection for response latency estimation.  Journal of Neuroscience Methods.  87(1).  13-16.
  • Priebe CE, Chen D (1998).  Spatial scan density estimates.  Proceedings of SPIE - The International Society for Optical Engineering.  3371.
  • Priebe CE, Cowen LJ (1998).  Mine detection via generalized Wilcoxon-Mann-Whitney classification.  Proceedings of SPIE - The International Society for Optical Engineering.  3392.
  • Solka JL, Wegman EJ, Priebe CE, Poston WL, Rogers GW (1998).  Mixture structure analysis using the Akaike Information Criterion and the bootstrap.  Statistics and Computing.  8(3).
  • Chen D, Priebe C (1998).  Spatial scan density estimates.  Proc. SPIE Vol. 3371.  3371.  295.
  • Friedman HS, Priebe CE (1998).  Estimating stimulus response latency.  Journal of Neuroscience Methods.  83(2).
  • Poston WL, Priebe C, Rogers GW, Solka JL, Wegman EJ (1998).  Mixture structure analysis using the Akaike Information Criterion and the bootstrap.  Statistics and Computing.  8(3).  177-188.
  • Friedman HS, Priebe C (1998).  Estimating stimulus response latency.  Journal of Neuroscience Methods.  83(2).  185-194.
  • Priebe CE, Olson TE, Healy DM (1997).  Exploiting stochastic partitions for minefield detection.  Proceedings of SPIE - The International Society for Optical Engineering.  3079.
  • Olson TE, Priebe CE, Olson TL (1997).  Detection and classification of mines via discriminant features and borrowed strength.  Proceedings of SPIE - The International Society for Optical Engineering.  3079.
  • Wallet BC, Solka JL, Priebe CE (1997).  A method for detecting microcalcifications in digital mammograms.  Journal of Digital Imaging.  10(3 SUPPL. 1).
  • Poston WL, Wegman EJ, Priebe CE, Solka JL (1997).  A deterministic method for robust estimation of multivariate location and shape.  Journal of Computational and Graphical Statistics.  6(3).
  • Priebe CE, Olson T, Healy DM (1997).  A spatial scan statistic for stochastic scan partitions.  Journal of the American Statistical Association.  92(440).
  • Priebe CE, Marchette DJ, Rogers GW (1997).  Segmentation of random fields via borrowed strength density estimation.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  19(5).
  • Jr, Dennis , Olson T, Priebe C (1997).  A Spatial Scan Statistic for Stochastic Scan Partitions.  Journal of the American Statistical Association.  92(440).  1476-1484.
  • Priebe CE, Marchette DJ, Rogers GW (1997).  Semiparametric nonhomogeneity analysis.  Journal of Statistical Planning and Inference.  59(1).
  • Cowen LJ, Priebe CE (1997).  Randomized Nonlinear Projections Uncover High-Dimensional Structure.  Advances in Applied Mathematics.  19(3).
  • Cowen LJ, Priebe C (1997).  Randomized nonlinear projections uncover high-dimensional structure.  Advances in Applied Mathematics.  19(3).  319-331.
  • Poston W, Priebe C, Solka J, Wegman E (1997).  A Deterministic Method for Robust Estimation of Multivariate Location and Shape.  Journal of Computational and Graphical Statistics.  6(3).  300-313.
  • Marchette DJ, Lorey RA, Priebe CE (1997).  An analysis of local feature extraction in digital mammography.  Pattern Recognition.  30(9).
  • Lorey RA, Marchette DJ, Priebe C (1997).  An analysis of local feature extraction in digital mammography.  Pattern Recognition.  30(9).  1547-1554.
  • Priebe C, Solka JL, Wallet BC (1997).  A method for detecting microcalcifications in digital mammograms.  Journal of digital imaging : the official journal of the Society for Computer Applications in Radiology.  10(3 Suppl 1).  136-139.
  • Marchette DJ, Priebe C, Rogers GW (1997).  Segmentation of random fields via borrowed strength density estimation.  IEEE transactions on pattern analysis and machine intelligence.  19(5).  494-499.
  • Marchette DJ, Priebe C, Rogers GW (1997).  Semiparametric nonhomogeneity analysis.  Journal of Statistical Planning and Inference.  59(1).  45-60.
  • Rogers GW, Olson TE, Priebe CE, Marchette DJ (1996).  Imposed measure approach to stochastic clutter characterization.  Proceedings of SPIE - The International Society for Optical Engineering.  2823.
  • Priebe CE (1996).  Nonhomogeneity analysis using borrowed strength.  Journal of the American Statistical Association.  91(436).
  • Priebe C (1996).  Nonhomogeneity Analysis Using Borrowed Strength.  Journal of the American Statistical Association.  91(436).  1497-1503.
  • Marchette DJ, Priebe CE, Rogers GW, Solka JL (1996).  Filtered kernel density estimation.  Computational Statistics.  11(2).
  • Marchette DJ, Priebe C, Rogers GW, Solka JL (1996).  Filtered kernel density estimation.  Computational Statistics.  11(2).  95-112.
  • Poston WL, Priebe CE, Holland OT (1995).  Maximizing the fisher information matrix in discrete-time systems.  Control and Dynamic Systems.  71(C).
  • Hayes HI, Priebe CE, Rogers GW, Marchette DJ, Solka JL, Lorey RA (1995).  Improved texture discrimination and image segmentation with boundary incorporation.  Proceedings of SPIE - The International Society for Optical Engineering.  2485.
  • Priebe C, Rogers GW, Solka JL (1995).  A Pdp Approach to Localized Fractal Dimension Computation with Segmentation Boundaries.  Simulation.  65(1).  26-36.
  • Rogers GW, Solka JL, Priebe CE (1995).  PDP approach to localized fractal dimension computation with segmentation boundaries.  Simulation.  65(1).
  • Lorey RA, Solka JL, Rogers GW, Marchette DJ, Priebe CE (1995).  Mammographic Computer-Assisted Diagnosis using Computational Statistics Pattern Recognition.  Real-Time Imaging.  1(2).
  • Lorey RA, Marchette DJ, Priebe C, Rogers GW, Solka JL (1995).  Mammographic Computer-Assisted Diagnosis using Computational Statistics Pattern Recognition..  Real-Time Imaging ().  1(2).  95-104.
  • Solka JL, Poston WL, Priebe CE, Rogers GW, Lorey RA, Marchette DJ, Woods K, Bowyer K (1994).  Detection of micro-calcifications in mammographic images using high dimensional features.  Proceedings of the IEEE Symposium on Computer-Based Medical Systems.
  • Priebe CE, Rogers GW, Marchette DJ, Solka JL (1994).  Change point analysis with adaptive mixture models.  International Geoscience and Remote Sensing Symposium (IGARSS).  3.
  • Priebe C (1994).  Adaptive Mixtures.  Journal of the American Statistical Association.  89(427).  796-806.
  • Priebe CE, Solka JL, Lorey RA, Rogers GW, Poston WL, Kallergi M, Oian W, Clarke LP, Clark RA (1994).  The application of fractal analysis to mammographic tissue classification.  Cancer Letters.  77(2-3).
  • Poston WL, Priebe C, Rogers GW, Solka JL (1994).  A Qualitative-Analysis of the Resistive Grid Kernel Estimator.  Pattern Recognition Letters.  15(3).  219-225.
  • Clark R, CLARKE LP, KALLERGI M, Lorey RA, Poston WL, Priebe C, QIAN W, Rogers GW, Solka JL (1994).  The Application of Fractal Analysis to Mammographic Tissue Classification.  Cancer Letters.  77(2-3).  183-189.
  • Priebe CE (1994).  Adaptive mixtures.  Journal of the American Statistical Association.  89(427).
  • Poston WL, Rogers GW, Priebe CE, Solka JL (1994).  A qualitative analysis of the resistive grid kernel estimator.  Pattern Recognition Letters.  15(3).
  • Solka JL, Priebe CE, Rogers GW (1993).  Initial assessment of discriminant surface complexity for power law features using adaptive mixture neural networks.  Proceedings of SPIE - The International Society for Optical Engineering.  1721.
  • Priebe CE, Marchette DJ, Rogers GW, Solka JL (1993).  Kernel estimators and mixture models in artificial neural networks.  Proceedings of SPIE - The International Society for Optical Engineering.  1721.
  • Rogers GW, Szu HH, Priebe CE, Solka JL (1993).  Nonparametric density estimation by a self-consistent neural network.  Proceedings of the International Joint Conference on Neural Networks.  2.
  • Rogers GW, Priebe CE, Marchette DJ, Solka JL (1993).  Adaptive mixture neural networks for functional estimation.  Proceedings of SPIE - The International Society for Optical Engineering.  1721.
  • Rogers G, Szu H, Solka J, Priebe C (1993).  Simple examples of artificial neuron models with internal dynamical degrees of freedom.  Proceedings of SPIE - The International Society for Optical Engineering.  1721.
  • Bowyer KW, Clarke LP, Doss CC, Priebe C, Solka JL, Woods KS (1993).  Comparative evaluation of pattern recognition techniques for detection of microcalcifications.  Proc. SPIE Vol. 1905.  1905.  841.
  • Marchette DJ, Priebe C (1993).  Adaptive Mixture Density-Estimation.  Pattern Recognition.  26(5).  771-785.
  • Priebe CE, Marchette DJ (1993).  Adaptive mixture density estimation.  Pattern Recognition.  26(5).
  • MALYEVAC DS, Priebe C, Rogers GW, SOLKA J (1993).  A Self-Organizing Network for Computing a Posteriori Conditional Class Probability.  Ieee Transactions on Systems Man and Cybernetics Part a-Systems and Humans.  23(6).  1672-1682.
  • Rogers GW, Solka J, Malyevac DS, Priebe CE (1993).  A Self-Organizing Network for Computing A Posteriori Conditional Class Probability.  IEEE Transactions on Systems, Man and Cybernetics.  23(6).
  • Poston WL, Priebe CE, Rogers GW, Solka JL (1992).  Vector quantization network for the estimation of probability density functions.  Intelligent Engineering Systems Through Artificial Neural Networks.  2.
  • Rogers GW, Poston WL, Priebe CE, Solka JL (1992).  Estimating discontinuous probability densities using a resistive grid kernel estimator.  Intelligent Engineering Systems Through Artificial Neural Networks.  2.
  • Priebe C, Rogers GW, Solka JL, Szu HH (1992).  Optoelectronic computation of waveletlike-based features.  Optical Engineering 31(09).  31.  1886.
  • Solka JL, Priebe CE, Rogers GW (1992).  Initial assessment of discriminant surface complexity for power law features.  Simulation.  58(5).
  • Priebe C, Rogers GW, Solka JL (1992).  An Initial Assessment of Discriminant Surface Complexity for Power Law Features.  Simulation.  58(5).  311-318.
  • Marchette DJ, Priebe C (1991).  Adaptive Mixtures - Recursive Nonparametric Pattern-Recognition.  Pattern Recognition.  24(12).  1197-1209.
  • Priebe CE, Marchette DJ (1991).  Adaptive mixtures: Recursive nonparametric pattern recognition.  Pattern Recognition.  24(12).
  • Marchette DJ, Priebe CE (1990).  The Adaptive Kernel Neural Network.  Mathematical and Computer Modelling.  14(C).
  • Marchette DJ, Priebe C (1990).  The Adaptive Kernel Neural Network.  Mathematical and Computer Modelling.  14.  328-333.
  • Priebe CE, Marchette DJ (1989).  Temporal pattern recognition: A network architecture for multi-sensor fusion.  Proceedings of SPIE - The International Society for Optical Engineering.  1002.
  • Priebe C (1988).  Temporal information processing: Word recognition.  Neural Networks.  1(1 SUPPL).
  • Sung CH, Priebe C, Marchette D (1988).  Temporal knowledge: Recognition and learning of time-based patterns.  Neural Networks.  1(1 SUPPL).
  • Sung CH, Priebe CE (1988).  Temporal pattern recognition.
  • Priebe CE, Athreya A, Lyzinski V, Marchette DJ, Sussman DL, Tang M (2014).  A limit theorem for scaled eigenvectors of random dot product graphs.  Sankhya.
  • Priebe C (2015).  A model selection approach for clustering a multinomial sequence with non-negative factorization.
  • Priebe C, Lyzinski V, Park Y, Trosset MW (2016).  Fast Embedding for JOFC Using the Raw Stress Criterion.  Journal of Computational and Graphical Statistics.
  • Vogelstein J, Priebe C (2013).  Shuffled Graph Classification: Theory and Connectome Applications.  Journal of Classification.
  • Priebe C, Qin Y (2016).  Robust Hypothesis Testing via Lq-Likelihood.  Statistica Sinica.
  • Priebe C, Lyzinski V, Sussman D, Athreya D, Park Y (2016).  Community Detection and Classification in Hierarchical Stochastic Blockmodels.  IEEE Transactions on Network Science and Engineering.
  • Priebe C, Tang M, Athreya D, D. L. Sussman , V. Lyzinski (2015).  A Nonparametric Two-Sample Hypothesis Testing for Random Dot Product Graphs.  Bernoulli Journal.
  • Priebe C, Zheng D, Park Y, Lyzinski V, Vogelstein J, Burns R (2016).  Semi-External Memory Sparse Matrix Multiplication for Billion-Node Graphs.  IEEE Transactions on Parallel and Distributed Systems.
  • Trosset MW, Gao M (2016).  On the Power of Likelihood Ratio Tests in Dimension-Restricted Submodels.
  • Priebe C, Athreya D, V. Lyzinski , D. J. Marchette , D. L. Sussman , M. Tang (2016).  A limit theorem for scaled eigenvectors of random dot product graphs.  Sankhya.  78-A(1).  1-18.
  • Priebe C, Tang M (2016).  Limit Theorems for Eigenvectors of the Normalized Laplacian for Random Graphs.
  • Priebe C, S. Adali (2015).  Fidelity-Commensurability Tradeoff in Joint Embedding of Disparate Dissimilarities.  Journal of Classification.  33(3).  485-506.
  • Priebe C, Fishkind D, C. Shen , Y. Park (2015).  On the Incommensurability Phenomenon.  Journal of Classification.
  • Priebe C, L. Chen , J. T. Vogelstein , V. Lyzinski (2016).  A Joint Graph Inference Case Study: the C.elegans Chemical and Electrical Cennectomes.  Worm.  5(2).  1.
  • Priebe C, Tang R, Ketcha M, Vogelstein J, Sussman DL (2016).  Law of Large Graphs.
  • Priebe C, Eichler K, Li F, Park Y, Andrade I, Schneider-Mizell C, Huser A, Saumweber T, Huser A, Bonnery D, Gerber B, Fetter RD, Truman JW, Abbott LF, Thum A, Zlatic M, Cardona A (2016).  The Complete Wiring Diagram of a High-Order Learning and Memory Center, the Insect Mushroom Body.  Nature.
  • Priebe C, J. T. Vogelstein , J. M. Conroy , V. Lyzinski , L. J. Podrazik , S. G. Kratzer , E. T. Harley , D. E. Fishkind , R. J. Vogelstein (2015).  Fast Approximate Quadradic Programming for Large (Brain) Graph Matching.
  • Priebe C, W. G. Roncal , D. M. Kleissas , J. T. Vogelstein , R. Burns , P. Manavalan , R. J. Vogelstein , M. A. Chevillet , Hager G (2015).  An Automated Images-To-Graphs Pipeline For High Resolution Connectomics.
  • Priebe C, Athreya D, Tang M, Lyzinski V, Park Y, Lewis B, Kane M (2016).  Numerical Tolerance for Spectral Decompositions of Random Dot Product Graphs.
  • Priebe C, Shen C, Chen L (2015).  Sparse Representation Classification Beyond L1 Minimization and the Subspace Assumption.
  • Priebe C, Yoder J (2015).  A Model-Based Semi-Supervised Clustering Methodology.
  • Priebe C, Shen C (2015).  Manifold Matching using Shortest-Path Distance and Joint Neighborhood Selection.
  • Priebe C, Yoder J (2016).  Semi-supervised K-means++.
  • Priebe C, V. Lyzinski , Fishkind D, M. Fiori , Vogelstein J, G. Sapiro (2015).  Graph Matching: Relax at Your Own Risk.
  • Priebe C, Tang M, Athreya D, Sussman D, Lyzinski V, Park Y (2016).  A Semiparametric Two-Sample Hypothesis Testing for Random Dot Product Graphs.  Journal of Computational and Graphical Statistics.
Conference Proceedings
  • Priebe C, Campbell WM, Li L, Acevedo-Aviles J, Dagli C, Campbell JP, Greyer K (2016).  Cross-Domain Entity Resolution in Social Media.  The 4th International Workshop on Natural Language Processing for Social Media.
  • Priebe C, Zheng D, Burns R, Vogelstein J, Szakay AS (2016).  An SSD-based Eigensolver for Spectral Analysis on Billion-Node Graph.  CoRR.
  • Priebe C (2015).  Community Detection and Classification in Hierarchical Stochastic Blockmodels.  Dartmouth College.
  • Priebe C (2015).  Learning Statistical Manifolds for Subsequent Inference: A Duet.  Indiana University.
  • Priebe C, Park Y, Wang H, No¨bauer T (2015).  Anomaly Detection on Whole-Brain Functional Imaging of Neuronal Activity using Graph Scan Statistics.  21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining: Workshop on Outlier Definition, Detection, and Description.
  • Priebe C (2015).  Big Data & Statistics at University of Costa Rica.
  • Priebe C, Wang H, Zheng D, Burns R (2015).  Active Community Detection in Massive Graphs.  SDM- Networks 2015: The Second SDM Workshop on Mining Networks and Graphs: A Big Data Analytic Challenge.
  • Priebe C (2015).  Community Detection and Classification in Hierarchical Stochastic Blockmodels.  Statistical and Computational Challenges in Networks and Cybersecurity.
  • Priebe C, Vogelstein J, Bogovic J, Carass A, Gray WR, Prince JL, Bennett L, Ferrucci L, Resnick SM, Vogelstein RJ (2015).  Graph-Theoretical Methods for Statistical Inference on MR Connectome Data.  OHBM.
  • Priebe C, Zheng D, Mhembere D, Burns R, Vogelstein J, Szalay AS (2015).  FlashGraph: Processing Billion-Node Graphs on an Array of Commodity SSDs.  In 13th USENIX Conference on File and Storage Technologies (FAST 15).
  • Mhembere D, Gray Roncal W, Sussman D, Priebe C, Jung R, Ryman S, Vogelstein RJ, Vogelstein J, Burns R (2013).  Computing Scalabal Multiavriate Global Invariants of Large (Brain-) Graphs.  Global Conference on Signal and Information Processing (GlobalSIP).  297-300.
  • Vogelstein J, Gray WR, Martin J, Coppersmith G, Dredze M, Bogovic J, Prince J, Resnick SM, Priebe C, Vogelstein RJ (2011).  Connectome classification using statistical graph theory and machine learning.  Annual Meeting of the Society for Neuroscience.
  • Vogelstein J, Gray W, Vogelstein RJ, Bogovic J, Resnick S, Prince J, Priebe C (2011).  Connectome classification: statistical graph theoretic methods for analysis of MR-connectome data.  Annual Meeting of the Organization for Human Brain Mapping.
  • Vogelstein J, Bogovic J, Carass A, Gray WR, Prince J, Landman B, Pham D, Ferrucci L, Resnick SM, Priebe C, others (2010).  Graph-Theoretical Methods for Statistical Inference on MR Connectome Data.  Annual Meeting of the Organization for Human Brain Mapping, Barcelona.
  • Zhou H, Karakos D, Khudanpur S, Andreou A, Priebe C (2009).  On projections of Gaussian distributions using maximum likelihood criteria.  Proceedings of the 2009 Information Theory and Applications Workshop (ITAW).  1-5.
  • Carliles S, Budavari T, Heinis S, Priebe C, Szalay S (2008).  Photometric Redshift Estimation on SDSS Data Using Random Forests.  Astronomical Data Analysis Software and Systems XVII.  394.  521.
  • Karakos D, Eisner J, Khudanpur S, Priebe C (2007).  Cross-Instance Tuning of Unsupervised Document Clustering Algorithms.  Human Language Technologies: Proceedings of the Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT).  252-259.
  • Karakos D, Khudanpur S, Eisner J, Priebe C (2007).  Iterative Denoising Using Jensen-Renyí­ Divergences with an Application to Unsupervised Document Categorization.  Proceedings of the International Conference on Acoustics, Speech and Signal Processing (ICASSP).
  • Karakos D, Khudanpur S, Eisner J, Priebe C (2005).  Unsupervised Classification via Decision Trees: An Information-Theoretic Perspective.  Proceedings of the 2005 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).  5.  1081-1084.
Back to top