Larry Wasserman - Publications

Affiliations: 
Carnegie Mellon University, Pittsburgh, PA 
Area:
Statistics

82 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2018 Liu S, Ginzberg MB, Patel N, Hild M, Leung B, Li Z, Chen YC, Chang N, Wang Y, Tan C, Diena S, Trimble W, Wasserman L, Jenkins JL, Kirschner MW, et al. Size uniformity of animal cells is actively maintained by a p38 MAPK-dependent regulation of G1-length. Elife. 7. PMID 29595474 DOI: 10.7554/eLife.26947  0.4
2016 Chen YC, Genovese CR, Wasserman L. A comprehensive approach to mode clustering Electronic Journal of Statistics. 10: 210-241. DOI: 10.1214/15-EJS1102  0.8
2016 Chen YC, Genovese CR, Tibshirani RJ, Wasserman L. Nonparametric modal regression Annals of Statistics. 44: 489-514. DOI: 10.1214/15-AOS1373  0.8
2015 Robins JM, Hernán MA, Wasserman L. Discussion of "On Bayesian estimation of marginal structural models". Biometrics. 71: 296-9. PMID 25652314 DOI: 10.1111/biom.12273  0.8
2015 Chen YC, Genovese CR, Wasserman L. Asymptotic theory for density ridges Annals of Statistics. 43: 1896-1928. DOI: 10.1214/15-AOS1329  0.8
2015 Genovese CR, Perone-Pacifico M, Verdinelli I, Wasserman L. Non-parametric inference for density modes Journal of the Royal Statistical Society. Series B: Statistical Methodology. DOI: 10.1111/rssb.12111  0.8
2015 Zhang Y, Padman R, Wasserman L, Patel N, Teredesai P, Xie Q. On clinical pathway discovery from electronic health record data Ieee Intelligent Systems. 30: 70-75. DOI: 10.1109/MIS.2015.14  0.8
2015 Vinci G, Freeman P, Newman J, Wasserman L, Genovese C. Estimating the distribution of Galaxy Morphologies on a continuous space Proceedings of the International Astronomical Union. 10: 68-71. DOI: 10.1017/S1743921314013568  0.8
2015 Lei J, Rinaldo A, Wasserman L. A conformal prediction approach to explore functional data Annals of Mathematics and Artificial Intelligence. 74: 29-43. DOI: 10.1007/s10472-013-9366-6  0.8
2015 Ramdas A, Reddi SJ, Póczos B, Singh A, Wasserman L. On the decreasing power of kernel and distance based nonparametric hypothesis tests in high dimensions Proceedings of the National Conference On Artificial Intelligence. 5: 3571-3577.  0.8
2015 Kandasamy K, Krishnamurthy A, Póczos B, Wasserman L, Robins JM. Nonparametric von Mises estimators for entropies, divergences and mutual informations Advances in Neural Information Processing Systems. 2015: 397-405.  0.8
2015 Azizyan M, Singh A, Wasserman L. Efficient sparse clustering of high-dimensional non-spherical Gaussian mixtures Journal of Machine Learning Research. 38: 37-45.  0.8
2015 Krishnamurthy A, Kandasamy K, Poczós B, Wasserman L. On estimating L2 2 divergence Journal of Machine Learning Research. 38: 498-506.  0.8
2015 Chazal F, Fasy BT, Lecci F, Michel B, Rinaldo A, Wasserman L. Subsampling methods for persistent homology 32nd International Conference On Machine Learning, Icml 2015. 3: 2133-2141.  0.8
2015 Lecci F, Rinaldo A, Wasserman L. Statistical analysis of metric graph reconstruction Journal of Machine Learning Research. 15: 3425-3446.  0.8
2015 Chen YC, Genovese CR, Ho S, Wasserman L. Optimal ridge detection using coverage risk Advances in Neural Information Processing Systems. 2015: 316-324.  0.8
2015 Reddi SJ, Ramdas A, Póczos B, Singh A, Wasserman L. On the high dimensional power of a linear-time two sample test under mean-shift alternatives Journal of Machine Learning Research. 38: 772-780.  0.8
2014 Zhang Y, Padman R, Wasserman L. On Learning and Visualizing Practice-based Clinical Pathways for Chronic Kidney Disease. Amia ... Annual Symposium Proceedings / Amia Symposium. Amia Symposium. 2014: 1980-9. PMID 25954471  0.52
2014 Wasserman L, Kolar M, Rinaldo A. Berry-Esseen bounds for estimating undirected graphs Electronic Journal of Statistics. 8: 1188-1224. DOI: 10.1214/14-EJS928  0.8
2014 Fasy BT, Lecci F, Rinaldo A, Wasserman L, Balakrishnan S, Singh A. Confidence sets for persistence diagrams Annals of Statistics. 42: 2301-2339. DOI: 10.1214/14-AOS1252  0.8
2014 Wasserman L. Discussion: "A significance test for the lasso" Annals of Statistics. 42: 501-508. DOI: 10.1214/13-AOS1175E  0.8
2014 Chazal F, Fasy BT, Lecci F, Rinaldo A, Wasserman L. Stochastic convergence of persistence landscapes and silhouettes Proceedings of the Annual Symposium On Computational Geometry. 474-483. DOI: 10.1145/2582112.2582128  0.8
2014 Lei J, Wasserman L. Distribution-free prediction bands for non-parametric regression Journal of the Royal Statistical Society. Series B: Statistical Methodology. 76: 71-96. DOI: 10.1111/rssb.12021  0.8
2014 Cisewski J, Croft RAC, Freeman PE, Genovese CR, Khandai N, Ozbek M, Wasserman L. Non-parametric 3D map of the intergalactic medium using the lyman-alpha forest Monthly Notices of the Royal Astronomical Society. 440: 2599-2609. DOI: 10.1093/mnras/stu475  0.8
2014 Krishnamurthy A, Kandasamy K, Póczos B, Wasserman L. Nonparametric estimation of rényi divergence and friends 31st International Conference On Machine Learning, Icml 2014. 3: 2550-2571.  0.8
2014 Ramdas A, Poczos B, Singh A, Wasserman L. An analysis of active learning with uniform feature noise Journal of Machine Learning Research. 33: 805-813.  0.8
2013 Lei J, Robins J, Wasserman L. Distribution Free Prediction Sets. Journal of the American Statistical Association. 108: 278-287. PMID 25237208 DOI: 10.1080/01621459.2012.751873  0.8
2013 Azizyan M, Singh A, Wasserman L. Density-sensitive semisupervised inference Annals of Statistics. 41: 751-771. DOI: 10.1214/13-AOS1092  0.8
2013 Hall R, Rinaldo A, Wasserman L. Differential privacy for functions and functional data Journal of Machine Learning Research. 14: 703-727.  0.8
2013 Balakrishnan S, Narayanan S, Rinaldo A, Singh A, Wasserman L. Cluster trees on manifolds Advances in Neural Information Processing Systems 0.8
2013 Azizyan M, Singh A, Wasserman L. Minimax theory for high-dimensional Gaussian mixtures with sparse mean separation Advances in Neural Information Processing Systems 0.8
2013 Póczos B, Rinaldo A, Singh A, Wasserman L. Distribution-free distribution regression Journal of Machine Learning Research. 31: 507-515.  0.8
2012 Zhao T, Liu H, Roeder K, Lafferty J, Wasserman L. The huge Package for High-dimensional Undirected Graph Estimation in R. Journal of Machine Learning Research : Jmlr. 13: 1059-1062. PMID 26834510  0.8
2012 Lafferty J, Liu H, Wasserman L. Sparse nonparametric graphical models Statistical Science. 27: 519-537. DOI: 10.1214/12-STS391  0.8
2012 Genovese CR, Perone-Pacifico M, Verdinelli I, Wasserman L. Manifold estimation and singular deconvolution under hausdorff loss Annals of Statistics. 40: 941-963. DOI: 10.1214/12-AOS994  0.8
2012 Wasserman L. Comment Journal of the American Statistical Association. 107: 1035-1036. DOI: 10.1080/01621459.2012.711729  0.8
2012 Genovese CR, Perone-Pacifico M, Isabella V, Wasserman L. The geometry of nonparametric filament estimation Journal of the American Statistical Association. 107: 788-799. DOI: 10.1080/01621459.2012.682527  0.8
2012 Liu H, Lafferty J, Wasserman L. Exponential concentration for mutual information estimation with application to forests Advances in Neural Information Processing Systems. 4: 2537-2545.  0.8
2012 Liu H, Han F, Yuan M, Lafferty J, Wasserman L. The nonparanormal SKEPTIC Proceedings of the 29th International Conference On Machine Learning, Icml 2012. 2: 1415-1422.  0.8
2012 Genovese CR, Jin J, Wasserman L, Yao Z. A comparison of the lasso and marginal regression Journal of Machine Learning Research. 13: 2107-2143.  0.8
2012 Genovese CR, Perone-Pacifico M, Verdinelli I, Wasserman L. Minimax manifold estimation Journal of Machine Learning Research. 13: 1263-1291.  0.8
2012 Rinaldo A, Singh A, Nugent R, Wasserman L. Stability of density-based clustering Journal of Machine Learning Research. 13: 905-948.  0.8
2012 Balakrishnan S, Singh A, Rinaldo A, Sheehy D, Wasserman L. Minimax rates for homology inference Journal of Machine Learning Research. 22: 64-72.  0.8
2011 Percival D, Roeder K, Rosenfeld R, Wasserman L. STRUCTURED, SPARSE REGRESSION WITH APPLICATION TO HIV DRUG RESISTANCE. The Annals of Applied Statistics. 5: 628-644. PMID 21892380 DOI: 10.1214/10-AOAS428  0.8
2011 Wasserman L. Frasian inference Statistical Science. 26: 322-325. DOI: 10.1214/11-STS352  0.8
2011 Weyant A, Wood-Vasey M, Wasserman L, Freeman P. An unbiased method of modeling the local peculiar velocity field with type Ia supernovae Astrophysical Journal. 732. DOI: 10.1088/0004-637X/732/2/65  0.8
2011 Kolar M, Lafferty J, Wasserman L. Union support recovery in multi-task learning Journal of Machine Learning Research. 12: 2415-2435.  0.8
2011 Liu H, Xu M, Gu H, Gupta A, Lafferty J, Wasserman L. Forest density estimation Journal of Machine Learning Research. 12: 907-951.  0.8
2011 Liu H, Xu M, Gu H, Gupta A, Lafferty J, Wasserman L. Forest density estimation Journal of Machine Learning Research. 12: 907-951.  0.8
2010 Liu H, Roeder K, Wasserman L. Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models. Advances in Neural Information Processing Systems. 24: 1432-1440. PMID 25152607  0.8
2010 Wasserman L. Comment on article by Robert Bayesian Analysis. 5: 223-228. DOI: 10.1214/10-BA601A  0.8
2010 Rinaldo A, Wasserman L. Generalized density clustering Annals of Statistics. 38: 2678-2722. DOI: 10.1214/10-AOS797  0.8
2010 Lee AB, Wasserman L. Spectral connectivity analysis Journal of the American Statistical Association. 105: 1241-1255. DOI: 10.1198/jasa.2010.tm09754  0.8
2010 Wasserman L, Zhou S. A statistical framework for differential privacy Journal of the American Statistical Association. 105: 375-389. DOI: 10.1198/jasa.2009.tm08651  0.8
2010 Zhou S, Lafferty J, Wasserman L. Time varying undirected graphs Machine Learning. 80: 295-319. DOI: 10.1007/s10994-010-5180-0  0.8
2010 Liu H, Chen X, Lafferty J, Wasserman L. Graph-valued regression Advances in Neural Information Processing Systems 23: 24th Annual Conference On Neural Information Processing Systems 2010, Nips 2010 0.8
2009 Roeder K, Wasserman L. Genome-Wide Significance Levels and Weighted Hypothesis Testing. Statistical Science : a Review Journal of the Institute of Mathematical Statistics. 24: 398-413. PMID 20711421 DOI: 10.1214/09-STS289  0.8
2009 Wasserman L, Roeder K. HIGH DIMENSIONAL VARIABLE SELECTION. Annals of Statistics. 37: 2178-2201. PMID 19784398  0.52
2009 Genovese CR, Perone-Pacifico M, Verdinelli I, Wasserman L. On the path density of a gradient field Annals of Statistics. 37: 3236-3271. DOI: 10.1214/08-AOS671  0.8
2009 Wasserman L, Roeder K. High-dimensional variable selection Annals of Statistics. 37: 2178-2201. DOI: 10.1214/08-AOS646  0.8
2009 Genovese C, Freeman P, Wasserman L, Nichol R, Miller C. Inference for the dark energy equation of state using Type Ia Supernova data Annals of Applied Statistics. 3: 144-178. DOI: 10.1214/08-AOAS229  0.8
2009 Ravikumar P, Lafferty J, Liu H, Wasserman L. Sparse additive models Journal of the Royal Statistical Society. Series B: Statistical Methodology. 71: 1009-1030. DOI: 10.1111/j.1467-9868.2009.00718.x  0.8
2009 Zhou S, Lafferty J, Wasserman L. Compressed and privacy-sensitive sparse regression Ieee Transactions On Information Theory. 55: 846-866. DOI: 10.1109/TIT.2008.2009605  0.8
2009 Zhou S, Ligett K, Wasserman L. Differential privacy with compression Ieee International Symposium On Information Theory - Proceedings. 2718-2722. DOI: 10.1109/ISIT.2009.5205863  0.8
2009 Dannenberg RB, Wasserman L. Estimating the error distribution of a tap sequence without ground truth Proceedings of the 10th International Society For Music Information Retrieval Conference, Ismir 2009. 297-302.  0.8
2009 Liu H, Lafferty J, Wasserman L. Nonparametric regression and classification with joint sparsity constraints Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference. 969-976.  0.8
2009 Zhou S, Lafferty J, Wasserman L. Compressed regression Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference 0.8
2009 Lafferty J, Wasserman L. Statistical analysis of semi-supervised regression Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference 0.8
2009 Ravikumar P, Liu H, Lafferty J, Wasserman L. SpAM: Sparse additive models Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference 0.8
2009 Liu H, Lafferty J, Wasserman L. The nonparanormal: Semiparametric estimation of high dimensional undirected graphs Journal of Machine Learning Research. 10: 2295-2328.  0.8
2008 Wasserman L. Comment on article by Gelman Bayesian Analysis. 3: 463-466. DOI: 10.1214/08-BA318D  0.8
2008 Lee AB, Nadler B, Wasserman L. Rejoinder of: Treelets-an adaptive multi-scale basis for spare unordered data Annals of Applied Statistics. 2: 494-500. DOI: 10.1214/08-AOAS137REJ  0.8
2008 Genovese C, Wasserman L. Adaptive confidence bands Annals of Statistics. 36: 875-905. DOI: 10.1214/07-AOS500  0.8
2008 Lee AB, Nadler B, Wasserman L. Treelets-an adaptive multi-scale basis for sparse unordered data Annals of Applied Statistics. 2: 435-471. DOI: 10.1214/07-AOAS137  0.8
2008 Lafferty J, Wasserman L. Rodeo: Sparse, greedy nonparametric regression Annals of Statistics. 36: 28-63. DOI: 10.1214/009053607000000811  0.8
2008 Bamford SP, Rojas AL, Nichol RC, Miller CJ, Wasserman L, Genovese CR, Freeman PE. Revealing components of the galaxy population through non-parametric techniques Monthly Notices of the Royal Astronomical Society. 391: 607-616. DOI: 10.1111/j.1365-2966.2008.13963.x  0.8
2007 Roeder K, Devlin B, Wasserman L. Improving power in genome-wide association studies: weights tip the scale. Genetic Epidemiology. 31: 741-7. PMID 17549760 DOI: 10.1002/gepi.20237  0.8
2006 Roeder K, Bacanu SA, Wasserman L, Devlin B. Using linkage genome scans to improve power of association in genome scans. American Journal of Human Genetics. 78: 243-52. PMID 16400608 DOI: 10.1086/500026  0.8
2005 Rinaldo A, Bacanu SA, Devlin B, Sonpar V, Wasserman L, Roeder K. Characterization of multilocus linkage disequilibrium. Genetic Epidemiology. 28: 193-206. PMID 15637716 DOI: 10.1002/gepi.20056  0.8
2004 Handley D, Serban N, Peters D, O'Doherty R, Field M, Wasserman L, Spirtes P, Scheines R, Glymour C. Evidence of systematic expressed sequence tag IMAGE clone cross-hybridization on cDNA microarrays. Genomics. 83: 1169-75. PMID 15177570 DOI: 10.1016/j.ygeno.2003.12.010  0.8
2003 Devlin B, Roeder K, Wasserman L. Analysis of multilocus models of association. Genetic Epidemiology. 25: 36-47. PMID 12813725 DOI: 10.1002/gepi.10237  0.8
2003 Tzeng JY, Devlin B, Wasserman L, Roeder K. On the identification of disease mutations by the analysis of haplotype similarity and goodness of fit. American Journal of Human Genetics. 72: 891-902. PMID 12610778 DOI: 10.1086/373881  0.8
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