{"id":60,"date":"2016-09-04T16:06:28","date_gmt":"2016-09-04T20:06:28","guid":{"rendered":"https:\/\/sciencescosmaincms.cm.ucf.edu\/math\/mpensky\/?page_id=60"},"modified":"2026-03-09T16:57:31","modified_gmt":"2026-03-09T20:57:31","slug":"recent-publications","status":"publish","type":"page","link":"https:\/\/sciences.ucf.edu\/math\/mpensky\/recent-publications\/","title":{"rendered":"Recent Publications"},"content":{"rendered":"<h2>Books and Book Chapters:<\/h2>\n<ul>\n<li>Kotz, S., Lumelskii, Y., Pensky, M. (2003)<br \/><strong>The Stress-Strength Model and Its Generalizations. Theory and Applications.<\/strong><br \/>World Scientific Co., Singapore, 253 pp. \u00a0<strong><a href=\"https:\/\/books.google.com\/books?id=GIvm25GuAxEC&amp;dq=%E2%80%A2%09Kotz,+S.,+Lumelskii,+Y.,+Pensky,+M.+(2003)+++++++++++The+Stress-Strength+Model+and+Its+Generalizations.+Theory+and+Applications&amp;source=gbs_navlinks_s&amp;hl=en\">Google Books<\/a><\/strong><\/li>\n<li>Pensky, M. (2006)<br \/><strong>Frequentist optimality of Bayesian wavelet shrinkage rules.<br \/><\/strong>In &#8220;<em>Splines and Wavelets: Athens 2005<\/em>&#8220;. G. Chen and M.-J. Lai, eds.,<br \/>Nashboro Press, Brentwood, TN, 390&#8211;401.<\/li>\n<li>Pensky, M. (2007)<br \/><strong>Empirical Bayes estimation of reliability.<br \/><\/strong>In &#8220;<em>Encyclopedia of Statistics in Quality and Reliability<\/em>&#8220;,<br \/>F. Ruggery, R.\u00a0 Kenett, F.W.\u00a0 Faltin (eds)., Wiley, Chichester, UK,<br \/>559&#8211;606. \u00a0 <strong><a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/eqr083Published.pdf\">PDF<\/a><\/strong><\/li>\n<li>Angelini, C.,\u00a0\u00a0 De Canditiis, D.,\u00a0\u00a0 Pensky, M. (2012)<br \/><strong>Bayesian methods for time course microarray analysis: from genes&#8217; detection to clustering.<br \/><\/strong>In \u00a0<em><strong>Advanced Statistical Methods for the Analysis of Large Data-Sets<\/strong>,<br \/><\/em>Di Ciaccio, A., Coli, M., Angulo Ibanez, J. M. (Eds.) Springer,\u00a0 pp. 47-56.<\/li>\n<li>\u00a0Davis,\u00a0 J.,\u00a0 Pensky, M.\u00a0 (2014)<br \/><strong>Model Selection for Classification with a Large Number of Classes.<br \/><\/strong>In \u00a0<em>Topics in Nonparametric Statistics. Springer Proceedings in Mathematics &amp; Statistics, 74<\/em>,<br \/>Akritas, M.G., Lahiri, S.N., Politis, D.N.,\u00a0 Eds., pp. 251&#8211;258.<\/li>\n<\/ul>\n<h2>Research Papers:<\/h2>\n<h4>2000<\/h4>\n<ul>\n<li>Bhattacharyya,B.B, Li, X., Pensky, M., and Richardson, G.D. (2000)<br \/><strong>Testing for unit roots in nearly nonstationary spatial autoregressive process.<br \/><\/strong><em>Annals of the Institute of Statistical Mathematics<\/em>,\u00a0\u00a0 52, 71 &#8212; 83.<\/li>\n<li>Pensky,M., and\u00a0 Ni, P. (2000)<br \/><strong>Extended linear empirical Bayes estimation.<br \/><\/strong><em>Communications in Statistics &#8211; Theory and Methods<\/em>,\u00a0 29, 579 &#8212; 592.<\/li>\n<li>Pensky, M., and\u00a0 Kirtane, K. (2000)<br \/><strong>Linear empirical Bayes estimation in the case of the Wishart distribution.<br \/><\/strong><em>Communications in Statistics. Theory and Methods<\/em>,\u00a0 29, 1787&#8211;1799.<\/li>\n<li>Pensky, M. (2000)<br \/><strong>Adaptive wavelet empirical Bayes estimation of a location or a scale parameter.<br \/><\/strong><em>Journal of Statistical Planning and Inference<\/em>,\u00a0 90, 275 &#8211;292.<\/li>\n<li>Elhor,A., and\u00a0 Pensky, M. (2000)<br \/><strong>Bayesian\u00a0 estimators of locations of lightning events.<br \/><\/strong><em>Sankhya<\/em>,\u00a0 B62, 202 &#8212; 216.<\/li>\n<\/ul>\n<h4>2001<\/h4>\n<ul>\n<li>Pensky, M., and\u00a0 Vidakovic, B. (2001)<br \/><strong>On non-equally spaced wavelet regression.<br \/><\/strong><em>Annals of the Institute of Statistical Mathematics<\/em>,\u00a0 53, 681&#8211;690.<\/li>\n<\/ul>\n<h4>2002<\/h4>\n<ul>\n<li>Pensky, M.\u00a0 (2002)<br \/><strong>Locally adaptive wavelet empirical Bayes estimation of a location\u00a0 parameter,<br \/><\/strong><em>Annals of the Institute of Statistical Mathematics<\/em>,\u00a0 54, 83&#8211;99.<\/li>\n<li>Pensky, M. (2002)<br \/><strong>Density deconvolution based on wavelets with bounded supports.<br \/><\/strong><em>Statistics and Probability Letters<\/em>,\u00a0 56, 261&#8211;269.<\/li>\n<li>Singh, R.S.,\u00a0 and\u00a0 Pensky, M. \u00a0(2002)<br \/><strong>Non-parametric estimation of prior densities of multidimensional location and\u00a0scale parameters with rates and best possible.<br \/><\/strong><em>The\u00a0 Journal of Mathematical Sciences<\/em>. New Series, 1, 86&#8211;105.<\/li>\n<li>Pensky, M., and Zayed, A.I. (2002)<br \/><strong>Density deconvolution of different conditional distributions.<br \/><\/strong><em>Annals of the Institute of Statistical Mathematics<\/em>,\u00a0 54, 701&#8211;712.<\/li>\n<li>Pensky, M. (2002)<br \/><strong>A new approach to empirical Bayes estimation with errors in variables.<br \/><\/strong><em>Statistics and Decisions<\/em>,\u00a0 20, 225&#8211;240.<\/li>\n<\/ul>\n<h4>2003<\/h4>\n<ul>\n<li>Pensky, M. (2003)<br \/><strong>Rates of convergence of\u00a0\u00a0 empirical Bayes tests for a normal mean.<br \/><\/strong><em>Journal of Statistical Planning and Inference<\/em>,\u00a0 11, 181&#8211;196.<\/li>\n<li>Pensky, M. (2003)<br \/><strong>Estimation of probabilities of linear inequalities for\u00a0 independent elliptic\u00a0 random vectors.<br \/><\/strong><em>Sankhya<\/em>,\u00a0 65, 91&#8211;106. \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/MySankhyaPaper03.pdf\">PDF<\/a><\/li>\n<\/ul>\n<h4>2004<\/h4>\n<ul>\n<li>De Canditiis, D., Pensky, M. (2004)<br \/><strong>Discussion on the meeting on &#8220;Statistical approaches to inverse problems&#8221;.<br \/><\/strong><em>Journ. Roy. Statist. Soc., Ser<\/em>. B,\u00a0 66, 638&#8211;640.<\/li>\n<\/ul>\n<h4>2005<\/h4>\n<ul>\n<li>Pensky, M., Allotaibi, M.\u00a0 (2005)<br \/><strong>Generalization of linear empirical Bayes estimation via wavelet series.<br \/><\/strong><em>Statistics and Decisions<\/em>,\u00a0 23, 181&#8211;198. \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/StatDecis_2005.pdf\">PDF<\/a><\/li>\n<\/ul>\n<h4>2006<\/h4>\n<ul>\n<li>Amato, U., Antoniadis, A., Pensky, M. (2006)<br \/><strong>Wavelet kernel penalized estimation for non-equispaced design regression.<br \/><\/strong><em>Statistics and Computing<\/em>,\u00a0 16, 37&#8211;55. \u00a0\u00a0<a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/STCO-Published-2006.pdf\">PDF<\/a><\/li>\n<li>De Canditiis, D., Pensky, M. (2006)<br \/><strong>Simultaneous Wavelet Deconvolution in Periodic Setting.<br \/><\/strong><em>Scandinavian Journal of Statistics<\/em>,\u00a0 33, 293&#8211;306. \u00a0\u00a0<a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/ScandJOS-2006.pdf\">PDF<\/a><\/li>\n<li>\u00a0Pensky, M. (2006)<br \/><strong>Frequentist optimality of Bayesian wavelet shrinlkage rules\u00a0for Gaussian and non-Gaussian noise.<br \/><\/strong><em>Annals of Statistics<\/em>,\u00a0 34,\u00a0 769&#8211;807. \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/AOS0135_Published-2006.pdf\">PDF<\/a><\/li>\n<li>Heard, A., Pensky, M. (2006)<br \/><strong>Confidence intervals for reliabilty and quantile function with application to NASA\u00a0 Space Flight data.<br \/><\/strong><em>IEEE Transactions in Reliability<\/em>,\u00a0 55, 591&#8211;601. \u00a0 <strong><a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/PublishedIEEE-2006.pdf\">PDF<\/a><\/strong><\/li>\n<\/ul>\n<h4>2007<\/h4>\n<ul>\n<li>Pensky, M.,\u00a0\u00a0 Vidakovic, B. and De Canditiis, D. (2007)<br \/><strong>Bayesian decision theoretic scale-adaptive estimation of log-spectral density.<\/strong><br \/><em>Statistica Sinica<\/em>,\u00a0 17, 635&#8211;666. \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/SS-03-158Published-2007.pdf\">PDF<\/a><\/li>\n<li>Pensky, M., Sapatinas, T.\u00a0 (2007)<br \/><strong>Frequentist optimality of Bayes Factor estimators in wavelet regression models.<\/strong><br \/><em>Statistica Sinica<\/em>,\u00a0 17, 599&#8211;633. \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/SS-05-258Published-2007.pdf\">PDF<\/a><\/li>\n<li>Angelini, C.,\u00a0\u00a0 De Canditiis, D., Mutarelli, M., Pensky, M. (2007)<br \/><strong>Bayesian approach to estimation and testing in time course microarray experiments.<br \/><\/strong><em>Statistical Applications in Genetics and Molecular Biology<\/em>, 6, \\#1, Article 24, 1&#8211;30. \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/SAGMG_Published-2007.pdf\">PDF<\/a><\/li>\n<li>Abramovich, F.,\u00a0 Grinshtein, V., Pensky, M.\u00a0\u00a0 (2007)<br \/><strong>On optimality of Bayesian testimation in the normal means problem.<\/strong><br \/><em>Annals of Statistics<\/em>,\u00a0 35,\u00a0 2261&#8211;2286. \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/AOS0254-2007.pdf\">PDF<\/a><\/li>\n<li>Abramovich, F.,\u00a0\u00a0 Antoniadis, A.,\u00a0 Pensky, M. (2007)<br \/><strong>Estimation of piecewise-smooth functions by amalgamated bridge regression splines.<br \/><\/strong><em>Sankhya<\/em>,\u00a0 70, 1&#8211;27. \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/SankhyaPublished-2007.pdf\">PDF<\/a><\/li>\n<\/ul>\n<h4>2008<\/h4>\n<ul>\n<li>Bradshaw, D.J.,\u00a0 Pensky, M. (2008)<br \/>Decision theory based classification of high-dimensional vectors based on small samples.<br \/>Test, 17, 83\u2014100. \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/TestPublishedVersion-2008.pdf\">PDF<\/a><\/li>\n<li>Brownstein, N.,\u00a0\u00a0 Pensky, M. (2008)<br \/><strong>Application of transformations in parametric inference.<br \/><\/strong><em>Journal of Statistics Education<\/em>, 16, No. 1, 1&#8211;10.<br \/><a href=\"http:\/\/www.amstat.org\/publications\/jse\/jse_archive.htm#2008\">http:\/\/www.amstat.org\/publications\/jse\/jse_archive.htm#2008<\/a>\u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/JStatEduPublished-2008.pdf\">PDF<\/a><\/li>\n<li>Angelini, C., Cutillo, L.,\u00a0\u00a0 De Canditiis, D., Mutarelli, M., Pensky, M. (2008)<br \/><strong>BATS: a Bayesian user-friendly software for Analyzing Time Series microarray experiments.<\/strong><br \/>BMC: Bioinformatics,\u00a0 9, No. 415.<br \/>DOI: <a href=\"http:\/\/www.biomedcentral.com\/1471-2105\/9\/415\">http:\/\/www.biomedcentral.com\/1471-2105\/9\/415<\/a>\u00a0 \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/BATS_Published-2008.pdf\">PDF<\/a><\/li>\n<li>Crampton, W.G.R., Davis,\u00a0 J.K.,\u00a0 Lovejoy,\u00a0 N.R.,\u00a0 Pensky, M. (2008)<br \/><strong>Multivariate classification of animal communication signals: a simulation-based comparison\u00a0of alternative signal processing procedures, using electric fishes.<br \/><\/strong><em>Journal of Physiology \u2013 Paris<\/em>, 102, 304&#8211;321. \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/Crampton-etal-2008-J-Phys-Paris-Published-2008.pdf\">PDF<\/a><\/li>\n<\/ul>\n<h4>2009<\/h4>\n<ul>\n<li>Pensky, M., Sapatinas, T. (2009)<br \/><strong>Functional Deconvolution in a Periodic Setting: Uniform Case.<br \/><\/strong><em>Annals of Statistics,<\/em> 37, 73&#8211;104. . \u00a0 \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/AOS552_Published-2009.pdf\">PDF<\/a><\/li>\n<li>Angelini, C.,\u00a0\u00a0 De Canditiis, D.,\u00a0\u00a0 Pensky, M. (2009)<br \/><strong>Bayesian models for the two-sample time-course microarray experiments.<\/strong><br \/><em>Computational Statistics &amp; Data Analysis<\/em>,\u00a0 53, 1547&#8211;1565.\u00a0 . \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/CSDA_Published-2009.pdf\">PDF<\/a><\/li>\n<\/ul>\n<h4>2010<\/h4>\n<ul>\n<li>Bradshaw, D.J.,\u00a0 Pensky, M. (2010)<br \/><strong>SVM-like decision theoretical classification of high-dimensional vectors.<br \/><\/strong><em>Journ. Stat. Plan. Inf.<\/em>, <strong>140<\/strong>, 705 &#8212; 718. \u00a0 \u00a0 \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/JSPI_Publ_2010.pdf\">PDF<\/a><\/li>\n<li>Pensky, M., Sapatinas, T.\u00a0 (2010)<br \/><strong>On Convergence Rates Equivalency and Sampling Strategies in a Functional Deconvolution Model.<br \/><\/strong><em>Annals of Statistics<\/em>, <strong>38<\/strong>, 1793&#8211;1844. \u00a0 \u00a0 \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/AOS767_Published-2010.pdf\">PDF<\/a><\/li>\n<li>Song, D.,\u00a0\u00a0 Fedorenko, I.,\u00a0\u00a0 Pensky, M.,\u00a0\u00a0 Qian, W.,\u00a0 Tockman, M.,\u00a0 and\u00a0 Zhukov, T.\u00a0 (2010)<br \/><strong>Quantificational and Statistical Analysis of the Differences in Centrosomal Features\u00a0of Untreated Lung Cancer Cells and Normal Cells.<br \/><\/strong><em>Analytical and Quantitative Cytology and Histology<\/em>, 32, No. 5, article\u00a0 280 \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/AQCH_CentrosomePublished-2010.pdf\">PDF<\/a><strong><br \/><\/strong><\/li>\n<\/ul>\n<h4>2011<\/h4>\n<ul>\n<li>Angelini, C.,\u00a0\u00a0 De Canditiis, D.,\u00a0\u00a0 Pensky, M. (2011)<br \/><strong>Estimation and Testing in Time-course MicroarrayExperiments.\u00a0\u00a0<\/strong><br \/><em>Bayesian Modeling in Bioinformatics<\/em>.<br \/>Eds. Dey, D.K.,\u00a0 Ghosh, S., and\u00a0 Mallick,B.K.,Chapman and Hall\/CRC,\u00a0Boca Raton, pp. 1&#8211;26. \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/eqr083Published-2011.pdf\">PDF<\/a><\/li>\n<li>Pensky, M., Sapatinas, T. (2011)<br \/><strong>Multichannel Boxcar Deconvolution with Growing Number of Channels.\u00a0<\/strong><br \/><em>Electronic Journal of Statistics<\/em>,\u00a0\u00a0 5, 53&#8211;82 \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/EJS597_Published-2011.pdf\">PDF<\/a><\/li>\n<li>Davis, J.,\u00a0 Pensky, M.,\u00a0 and Crampton, W. (2011)<br \/><strong>Bayesian Feature Selection for Classification with Possibly Large Number of Classes.<\/strong><br \/><em>Journal of Statistical Planning and Inference<\/em>, <strong>141<\/strong>,\u00a0\u00a0 3256\u2013-3266 \u00a0 \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/JSPI_2011_Published-2011.pdf\">PDF<\/a><\/li>\n<li>Huo, Q.,\u00a0 Cordero, A.,\u00a0\u00a0\u00a0 Bogdanovic, J.,\u00a0\u00a0\u00a0 Colon, J.,\u00a0 Baker, C.H.,\u00a0\u00a0 Goodison, S.,\u00a0 Pensky, M. (2011)<br \/><strong>A Facile Nanoparticle Immunoassay to Detect Multiple Biomarkers in Serum Samples.<\/strong><br \/><em>Journal of Nanobiotechnology<\/em>,\u00a0 <strong>9<\/strong> (20)<br \/>DOI: <a href=\"http:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC3127990\/pdf\/1477-3155-9-20.pdf\">http:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC3127990\/pdf\/1477-3155-9-20.pdf<\/a><\/li>\n<\/ul>\n<h4>2012<\/h4>\n<ul>\n<li>Angelini, C.,\u00a0\u00a0 De Canditiis, D.,\u00a0\u00a0 Pensky, M. (2012)<br \/><strong>Clustering\u00a0 Time-Course Microarray Data Using\u00a0Functional Bayesian Infinite Mixture Model.<\/strong><br \/><em>Journal of Applied Statistics<\/em>, \u00a0<strong>39<\/strong>, 129-149. \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/Clustering_JAS2012Publ-2012.pdf\">PDF<\/a><\/li>\n<\/ul>\n<h4>\u00a02013<\/h4>\n<ul>\n<li>Klopp, O.,\u00a0 Pensky, M. (2013)<br \/>Non-asymptotic approach to varying coefficient model.<br \/><em>Electronic Journal of Statistics<\/em>, \u00a0<strong>7<\/strong>,\u00a0 454-479. \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/EJS2013_VarCoefPubl-2013.pdf\">PDF<\/a><\/li>\n<li>Abramovich, F., Pensky, M.,\u00a0 Rozenholc, Y. (2013)<br \/><strong>Laplace deconvolution with noisy observations.<\/strong><br \/><em>Electronic Journal of Statistics<\/em>, \u00a0<strong>7<\/strong>,\u00a0 1094\u20131128. \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/APR_EJS_2013_Publ-2013.pdf\">PDF<\/a><\/li>\n<li>Benhaddou, R., Pensky, M., Picard, D. (2013)<br \/><strong>Anisotropic Denoising in Functional Deconvolution Model with\u00a0Dimension-free Convergence Rates.<\/strong><br \/><em>Electronic Journal of Statistics<\/em>, \u00a0<strong>7<\/strong>,\u00a0 1686\u20131715. \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/EJS-Anisotropic-Published-2013.pdf\">PDF<\/a><\/li>\n<li>Benhaddou, R., Pensky, M.\u00a0 (2013)<br \/><strong>Adaptive\u00a0 Nonparametric Empirical Bayes Estimation Via Wavelet Series.<br \/><\/strong><em>Journ. Stat. Plan. Inference<\/em>, \u00a0<strong>143<\/strong>,\u00a0 1672\u20131688. \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/EB_JSPI_Published-2013.pdf\">PDF<\/a><\/li>\n<li>Pensky, M. (2013)<br \/><strong>Spatially inhomogeneous linear inverse problems with possible singularities.<\/strong><br \/><em>Annals of Statistics<\/em>, <strong>41<\/strong>, 2668&#8211;2697. \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/AOS1166-Published-2013.pdf\">PDF<\/a>\u00a0 \u00a0<a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/Inhomogeneous_Inverse-2013.zip\">SOFTWARE<\/a><\/li>\n<\/ul>\n<h4>2014<\/h4>\n<ul>\n<li>Antoniadis, A., Pensky, M., Sapatinas, T. (2014)<br \/><strong>Nonparametric Regression Estimation with Incomplete Data: Minimax Global Convergence Rates\u00a0\u00a0 and Adaptivity.<\/strong><br \/><em>ESAIM,<\/em> 18, 1-41. \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/ESAIM_2014-Published-2014.pdf\">PDF<\/a><\/li>\n<li>Benhaddou, R., Kulik, R., Pensky, M., Sapatinas, T. (2014)<br \/><strong>Multichannel Deconvolution with Long-Range Dependence: A Minimax Study. \u00a0 \u00a0<\/strong><br \/><em>Journ. Stat. Plan. Inference<\/em>,\u00a0 148, 1-19 (invited paper). \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/JSPI-5243-Published-2014.pdf\">PDF<\/a><\/li>\n<li>Davis, J., Pensky, M.\u00a0 (2014)<br \/><strong>Model Selection for Classification with a\u00a0Large Number of Classes.<\/strong><br \/>In: <em>Topics in Nonparametric Statistics.\u00a0Springer Proceedings in Mathematics &amp; Statistics<\/em>, <strong>74<\/strong>,<br \/>Akritas,M.G., Lahiri, S.N., Politis, D.N., Eds., 251\u2013258 \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/DavisPensky_ISNPS_Published-2014.pdf\">PDF<\/a><\/li>\n<\/ul>\n<h4>2015<\/h4>\n<ul>\n<li>Klopp,\u00a0\u00a0 O., Pensky, M. (2015)<br \/><strong>Sparse high-dimensional varying coefficient model:\u00a0non-asymptotic minimax study.\u00a0\u00a0<\/strong><br \/>Ann. Stat, 43,\u00a01273&#8211;1299. \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/VarCoefAOS2015_Published-2015.pdf\">PDF<\/a><\/li>\n<li>Liu, B., Wang, O., Tappen, M., Foroosh, H., Pensky, M. (2015)<br \/><strong>Sparse convolutional neural networks.<\/strong><br \/>CVPR Proceedings 2015,\u00a0\u00a0 806&#8211;814. \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/Liu_Sparse_Convolutional_Neural_2015_CVPR_Published-2015.pdf\">PDF<\/a><\/li>\n<li>Jaberi, M.,\u00a0\u00a0 Pensky, M., Foroosh, H. (2015)<br \/><strong>Sparse\u00a0 Withdrawal of Inliers in a First Trial (SWIFT).\u00a0<\/strong><br \/>CVPR Proceedings 2015,\u00a0 4849&#8211;4857. \u00a0 \u00a0<a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/Jaberi_SWIFT_Sparse_Withdrawal_2015_CVPR_Published-2015.pdf\">PDF<\/a><\/li>\n<\/ul>\n<h4>2016<\/h4>\n<ul>\n<li>Pensky, M.<br \/><strong>Solution of linear ill-posed problems using overcomplete\u00a0dictionaries. \u00a0<\/strong><br \/><em>Ann. Statist.<\/em>, 44, 1739-1764.\u00a0 <a href=\"http:\/\/Lasso_AOS1445_Published.pdf\">PDF<\/a><\/li>\n<li>De Canditiis, D.,\u00a0\u00a0 Pensky, M.<br \/><strong>Estimation of delta-contaminated density\u00a0of the random intensity\u00a0\u00a0 of Poisson data.<\/strong><br \/><em>Electronic Journal of Statistics<\/em>, 10,\u00a0 683-705. \u00a0\u00a0 <a href=\"https:\/\/projecteuclid.org\/euclid.ejs\/1458133058\">PDF<\/a><\/li>\n<li>Pensky, M.<br \/><strong>Minimax theory of estimation of linear functionals of the deconvolution density <\/strong><br \/><strong>with or without sparsity.\u00a0<\/strong> <em>Ann. Statist<\/em>., accepted\u00a0 <a href=\"http:\/\/AOS1505-030-Final.pdf\">PDF<\/a><\/li>\n<\/ul>\n<h4>2017<\/h4>\n<ul>\n<li>Comte,\u00a0 F., Cuenod,\u00a0 C.-A., Pensky, M.,\u00a0\u00a0 Rozenholc, Y. \u00a0(2017)<br \/><strong>Laplace deconvolution on the basis of\u00a0\u00a0 time domain data\u00a0 and its application to Dynamic Contrast Enhanced imaging. <\/strong><em>Journal of the Royal Stat. Society, Ser. B<\/em>,\u00a0<strong> 79<\/strong>,\u00a0\u00a0 69\u201394 \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/JRSS_B_2017_Published.pdf\">PDF<\/a><br \/><a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2016\/09\/Laguerre-Laplace-Deconvolution-2016.zip\">SOFTWARE<\/a>\u00a0(courtesy Yves Rozenholc)<\/li>\n<li>Pensky, M.<br \/><strong>Minimax theory of estimation of linear functionals of the deconvolution density <\/strong><br \/><strong>with or without sparsity.\u00a0<\/strong> <em>Ann. Statist<\/em>., <strong>45<\/strong>,\u00a0 1516\u20131541\u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2018\/02\/AOS2017-1498Published.pdf\">PDF<\/a><strong><br \/><\/strong><strong><br \/><\/strong><\/li>\n<\/ul>\n<ul>\n<li>\n<h4>2018<\/h4>\n<\/li>\n<\/ul>\n<ul>\n<li>Abramovich, F., De Canditiis, D., Pensky, M. (2018)\u00a0 <strong>Solution of linear ill-posed problems by model <\/strong><strong><strong>selection and aggregation.\u00a0<\/strong><\/strong> <em><strong>12<\/strong>, <\/em>1822-1841<em>. <\/em><a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2018\/08\/EJS2018_ExpWeights.pdf\">PDF<\/a><\/li>\n<\/ul>\n<ul>\n<li>D. De Canditiis, M. Pensky, P.J. Wolfe (2018)<br \/><strong>Denoising strategies for general finite frames<\/strong>. <em>Mathematics and Computers in Simulation<\/em>, <strong>147,<\/strong>\u00a0 90\u201399<a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2018\/02\/MATCOM2018_DanielaPatrick.pdf\">\u00a0\u00a0 PDF<\/a><\/li>\n<li>Gupta, P., Pensky, M.<br \/><strong>Solution of linear ill-posed problems using random dictionaries<\/strong>. <em>Sankhya, Ser. B, <\/em>\u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2018\/02\/Sankhya2018_Publ_Online.pdf\">PDF<\/a> \u00a0\u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2017\/06\/MatLabFiles.zip\">MatLabFiles<\/a><\/li>\n<li>Jaberi, M., Pensky, M., Foroosh, H. (2018) <strong>Probabilistic Sparse Subspace Clustering Using Delayed Association.<\/strong> <em>Proceedings of the 2018 24th International Conference<\/em><br \/><em>on Pattern Recognition (ICPR)<\/em>, 2087-2092.\u00a0<a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2019\/10\/ICPR_Paper_Final.pdf\"> PDF<\/a><\/li>\n<\/ul>\n<ul>\n<li>\n<h4>2019<\/h4>\n<\/li>\n<\/ul>\n<ul>\n<li>Abramovich, F., Pensky, M.\u00a0\u00a0 (2019)\u00a0 <strong>Classification with many classes: Challenges and pluses.<\/strong>\u00a0 <em>Journal of Multivariate Analysis<\/em>,<strong> 174<\/strong>,\u00a0 #104536. \u00a0<a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2019\/10\/yjmva104536.pdf\">PDF<\/a><\/li>\n<li>Pensky, M., Zhang, T. (2019) <strong>Spectral clustering in the dynamic stochastic block model<\/strong>. <em>Electronic Journal of Statistics,<\/em> <strong>13<\/strong>, 678-709\u00a0\u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2019\/10\/EJS2019_SpecClustPubl.pdf\">PDF<\/a><\/li>\n<li>Pensky, M. (2019)\u00a0 <strong>Dynamic network models and graphon estimation<\/strong>. <em>Ann. Statist.<\/em>, <strong>47,<\/strong> 2378\u20132403\u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2019\/10\/AOS_2019_DSBM_Published.pdf\">PDF<\/a><\/li>\n<li>Benhaddou, R., Pensky, M.,\u00a0 Rajapakshage, R. (2019)\u00a0 <strong>Anisotropic functional Laplace decnvolution<\/strong><strong>\u00a0 <\/strong><em>Journ. Statist. Plan. Inf.<\/em>, <strong>199<\/strong>, 271\u2013285.\u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2019\/10\/AFDL_JSPI2019_Published.pdf\">PDF<\/a><\/li>\n<li>Rimal, R., Pensky, M.\u00a0(2019) <strong>Density Deconvolution with Small Berkson Errors. <\/strong><em>Mathematical Methods of Statistics<\/em>, <strong>28<\/strong>, 208\u2013227.\u00a0 <a href=\"https:\/\/link.springer.com\/article\/10.3103\/S1066530719030025?wt_mc=Internal.Event.1.SEM.ArticleAuthorOnlineFirst&amp;utm_source=ArticleAuthorOnlineFirst&amp;utm_medium=email&amp;utm_content=AA_en_06082018&amp;ArticleAuthorOnlineFirst_20190928\">PDF<\/a><\/li>\n<li>Jaberi, M., Pensky, M., Foroosh, H. (2019)\u00a0 <strong>SWIFT: Sparse Withdrawal of Inliers in a First Trial<\/strong>. <em>IEEE Transactions on Pattern Analysis and Machine Intelligence<\/em>, \u00a0<strong>41<\/strong>, 3057 &#8211; 3070.\u00a0 \u00a0<a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2020\/06\/TRAMI_2019_Published.pdf\">PDF<\/a><\/li>\n<\/ul>\n<ul>\n<li>\n<h4>2020<\/h4>\n<\/li>\n<li>Rajapakshage, R., Pensky, M.\u00a0 (2020)\u00a0\u00a0 <strong>Clustering in statistical ill-posed linear inverse problems.<\/strong> <em>IEEE Transactions on Information Theory,\u00a0<\/em> <strong>66<\/strong>, 7180-7195\u00a0 <strong><a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2021\/07\/IEEE_InvClust_2020_Published.pdf\">PDF<\/a><\/strong><\/li>\n<li>\n<h4>2021<\/h4>\n<\/li>\n<li>Noroozi, M., Rimal, R., Pensky, M. (2021) <strong>Estimation and Clustering in Popularity Adjusted Stochastic Block Model.<\/strong>\u00a0<i> Journal of Royal Stat. Soc., Ser. B, <\/i><strong>83<\/strong><i>, <\/i>293-317<i>.<\/i>\u00a0 <strong><a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2021\/07\/JRSSB2021_PABM_Published.pdf\">PDF<\/a> <\/strong>\u00a0\u00a0 \u00a0<a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2020\/06\/PABM_MatLabCodes.zip\"><strong>MatLab Codes<\/strong><\/a><\/li>\n<li>Noroozi, M., Pensky, M. (2021) \u00a0<strong>Statistical Inference in Heterogeneous Block Model. The Hierarchy of Block Models.\u00a0 <em>Sankhya, Ser.A<\/em>., 84, 64-107<br \/><\/strong><em><span style=\"color: #0000ff\"><a style=\"color: #0000ff\" href=\"https:\/\/arxiv.org\/abs\/2002.02610\">ArXiv: 2002.02610<\/a>\u00a0 \u00a0 \u00a0<strong><a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2021\/10\/HBM_Matlab_Codes.zip\"><span style=\"color: #0000ff\">MatLab Codes<\/span><\/a><\/strong><\/span><\/em><\/li>\n<li>Noroozi, M., Rimal, R., Pensky, M.<strong> (2021)\u00a0 Sparse Popularity Adjusted Stochastic Block Model. <em>Journ. Machine Learn. Res., <\/em>22<\/strong><strong><em>, <\/em>1-36\u00a0 \u00a0 <a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2021\/10\/SPABM_Published.pdf\">PDF<\/a><\/strong>\u00a0<strong> \u00a0<a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2021\/10\/SPABM_Matlab_Codes.zip\"><em><span style=\"color: #0000ff\">MatLab Codes<\/span><\/em><\/a><\/strong><\/li>\n<li>Pensky, M. , Wang, Y. (2021)\u00a0 <strong>Clustering of Diverse Multiplex Networks. <\/strong>See Year 2024 for MatLab Code and Data Sets.\u00a0 <a href=\"https:\/\/arxiv.org\/pdf\/2110.05308v1.pdf\"><span style=\"color: #0000ff\"><strong><em>ArXiv:2110.05308<\/em><\/strong><\/span><\/a><\/li>\n<\/ul>\n<p><strong>\u00a0 \u00a0 \u00a0 2022<\/strong><\/p>\n<ul>\n<li>Fan, X., Pensky, M., Yu, F., Zhang, T. (2022)\u00a0 <strong>ALMA: Alternating Minimization Algorithm For Clustering Mixture Multilayer Network. \u00a0<\/strong><em>Journal of Machine Learning Research<\/em><strong>, 23<\/strong>, #330, 1-46.\u00a0 <strong><a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2023\/08\/ALMA_Published.pdf\">PDF<\/a><\/strong><\/li>\n<\/ul>\n<ul>\n<li>Pensky, M. (2022) <strong>Invited Discussion of \u201cConfidence Intervals for Nonparametric Empirical Bayes Analysis\u201d by Nikolaos Ignatiadis and Stefan Wager. <\/strong>\u00a0<em>Journal of the \u00a0American Statistical Association,<\/em> <strong>117<\/strong>, 1183&#8211;1185.\u00a0 <strong><a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2023\/08\/JASA2022_Published.pdf\">PDF<\/a><\/strong><\/li>\n<\/ul>\n<p><strong>2023<\/strong><\/p>\n<ul>\n<li>Pensky, M. (2023)\u00a0 Invited Discussion of &#8220;<strong>Vintage Factor Analysis with Varimax Performs Statistical Inference&#8221; by Karl Rohe and Muzhe Zeng<\/strong>. \u00a0<em>Journal of the Royal Statistical Society, Ser. B<\/em>,\u00a0 <strong>85<\/strong>, 1062-1066. <strong><a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2024\/01\/Pensky_Discussion_-Rohe_JRSSB_2023.pdf\">PDF<\/a><\/strong><strong style=\"font-size: revert;color: initial\">\u00a0\u00a0<\/strong><\/li>\n<\/ul>\n<p><strong>2024<\/strong><\/p>\n<ul>\n<li>Pensky, M. , Wang, Y. (2024)\u00a0 <strong>Clustering of Diverse Multiplex Networks. <\/strong><em>IEEE Transactions on Network Science and Engineering, <\/em><strong>11<\/strong>, 3441\u20133454<strong>.\u00a0 \u00a0<\/strong><em><strong><a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2024\/01\/DIMPLE_MatLab_Code_Data.zip\">MatLab Code and Data Sets<\/a><\/strong>\u00a0<\/em><\/li>\n<li>Pensky, M. , Noroozi, M. (2024)\u00a0 \u00a0<strong>Sparse Subspace Clustering in Diverse Multiplex Network Model. <\/strong><em>Journal of Multivariate Analysis<\/em>,<strong> 203, <\/strong># 105333. \u00a0<strong><em><span style=\"color: #0000ff\"><a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2024\/04\/JMVA_SSC_DIMPLE_Matlab_Code.zip\">MatLab Code and Data Sets<\/a><\/span><\/em><\/strong><\/li>\n<li>Pensky, M. (2024) <strong>Davis-Kahan Theorem in the two-to-infinity norm and its application<\/strong><br \/><strong>to perfect clustering<\/strong>. <em><a href=\"https:\/\/arxiv.org\/abs\/2411.11728\">ArXiv:2411.11728.<\/a><\/em><\/li>\n<\/ul>\n<p><strong>2025<\/strong><\/p>\n\n\n<ul>\n<li>Pensky, M. (2025)\u00a0<strong> Signed Diverse Multiplex Networks: Clustering and Inference<\/strong>. IEEE Transactions on Information Theory, <strong>70<\/strong>, 7076-7096.\u00a0 \u00a0 <strong><a href=\"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-content\/uploads\/sites\/9\/2025\/07\/SGRDPG_MatLab_Files.zip\">MatLab Code<\/a><\/strong>\u00a0 \u00a0<a href=\"https:\/\/arxiv.org\/abs\/2402.10242\"><span style=\"color: #0000ff\"><em>ArXiv:2402.10242<\/em><\/span><\/a><\/li>\n<li>Pensky, M. (2025) <strong>Perfect Clustering in Very Sparse Diverse Multiplex Networks<\/strong>.\u00a0 <strong><a href=\"https:\/\/arxiv.org\/abs\/2507.19423\"><span style=\"color: #3366ff\"><em>Arxiv:2507.19423<\/em><\/span><\/a><\/strong><\/li>\n<\/ul>\n\n\n\n<p><strong>2026<\/strong><\/p>\n<ul>\n<li>&nbsp;Bhadra,S., Pensky, M., Sengupta, S. (2026) <strong>Scalable community detection in massive<\/strong><br><strong>networks via predictive assignment<\/strong>. <i>Journal of the American Statistical Association, accepted.&nbsp;<\/i> <span style=\"color: #3366ff\"><strong><a style=\"color: #3366ff\" href=\"https:\/\/arxiv.org\/abs\/2503.16730\"><em>ArXiv:2503.16730<\/em><\/a><\/strong><\/span><\/li>\n<li>Dewage, K., Pensky, M., De Silva, S., Mondal, S. (2026) <strong>LORA-CRAFT: Cross-layer<\/strong><br><strong>Rank Adaptation via Frozen Tucker Decomposition of Pre-trained Attention Weights.<\/strong><br><a href=\"https:\/\/arxiv.org\/abs\/2602.17510\"><span style=\"color: #3366ff\"><strong><em>ArXiv:2602.17510<\/em><\/strong><\/span><\/a><\/li>\n<li>Gao, S., Lubberts, Z., Pensky, M. (2026) <strong>KRAFTY: Khatri-Rao Framework for Joint<\/strong><br><strong>Cluster Recovery. <a href=\"https:\/\/arxiv.org\/abs\/2603.04608\"><span style=\"color: #3366ff\"><em>ArXiv:2603.04608<\/em><\/span><\/a><\/strong><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n\n\n","protected":false},"excerpt":{"rendered":"<p>Books and Book Chapters: Kotz, S., Lumelskii, Y., Pensky, M. (2003)The Stress-Strength Model and Its Generalizations. Theory and Applications.World Scientific Co., Singapore, 253 pp. \u00a0Google Books Pensky, M. (2006)Frequentist optimality of Bayesian wavelet shrinkage rules.In &#8220;Splines and Wavelets: Athens 2005&#8220;. G. Chen and M.-J. Lai, eds.,Nashboro Press, Brentwood, TN, 390&#8211;401. Pensky, M. (2007)Empirical Bayes estimation [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"class_list":["post-60","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-json\/wp\/v2\/pages\/60","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-json\/wp\/v2\/comments?post=60"}],"version-history":[{"count":54,"href":"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-json\/wp\/v2\/pages\/60\/revisions"}],"predecessor-version":[{"id":442,"href":"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-json\/wp\/v2\/pages\/60\/revisions\/442"}],"wp:attachment":[{"href":"https:\/\/sciences.ucf.edu\/math\/mpensky\/wp-json\/wp\/v2\/media?parent=60"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}