CrossCat: A Fully Bayesian Nonparametric Method for Analyzing Heterogeneous, High Dimensional Data
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Joshua B. Tenenbaum | Patrick Shafto | Vikash K. Mansinghka | Eric Jonas | Vikash Mansinghka | Cap Petschulat | Max Gasner | J. Tenenbaum | Patrick Shafto | Cap Petschulat | Eric Jonas | Max Gasner
[1] Nicolas Ulmer,et al. The Cost Conundrum , 2010 .
[2] Russell S. Kirby,et al. The Dartmouth Atlas of Health Care , 1998 .
[3] G. Box. Robustness in the Strategy of Scientific Model Building. , 1979 .
[4] Yura N. Perov,et al. Venture: a higher-order probabilistic programming platform with programmable inference , 2014, ArXiv.
[5] M. Escobar,et al. Bayesian Density Estimation and Inference Using Mixtures , 1995 .
[6] Trevor Hastie,et al. Imputing Missing Data for Gene Expression Arrays , 2001 .
[7] H. Thompson,et al. Jump‐Diffusion Processes and the Term Structure of Interest Rates , 1988 .
[8] Haydn Bush,et al. The cost conundrum. , 2008, Hospitals & health networks.
[9] Nir Friedman,et al. Learning Hidden Variable Networks: The Information Bottleneck Approach , 2005, J. Mach. Learn. Res..
[10] N. Meinshausen,et al. High-dimensional graphs and variable selection with the Lasso , 2006, math/0608017.
[11] Ying Cui,et al. Non-redundant Multi-view Clustering via Orthogonalization , 2007, Seventh IEEE International Conference on Data Mining (ICDM 2007).
[12] L. Wasserman. Low Assumptions, High Dimensions , 2011 .
[13] Jiahui Wang,et al. A Bayesian Time Series Model of Multiple Structural Changes in Level, Trend, and Variance , 2000 .
[14] Carl E. Rasmussen,et al. The Infinite Gaussian Mixture Model , 1999, NIPS.
[15] John Geweke,et al. Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments , 1991 .
[16] Michael I. Jordan,et al. Multiple Non-Redundant Spectral Clustering Views , 2010, ICML.
[17] Robert Tibshirani,et al. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.
[18] Carl E. Rasmussen,et al. Factorial Hidden Markov Models , 1997 .
[19] Peter Green,et al. Markov chain Monte Carlo in Practice , 1996 .
[20] Peter Bühlmann,et al. Missing values: sparse inverse covariance estimation and an extension to sparse regression , 2009, Statistics and Computing.
[21] Radford M. Neal,et al. A Split-Merge Markov chain Monte Carlo Procedure for the Dirichlet Process Mixture Model , 2004 .
[22] Kaushik Ghosh,et al. Nested Partition Models , 2009 .
[23] R. Tibshirani,et al. Sparse inverse covariance estimation with the graphical lasso. , 2008, Biostatistics.
[24] David J. Hand,et al. Classifier Technology and the Illusion of Progress , 2006, math/0606441.
[25] Vikash K. Mansinghka,et al. Cross-Categorization : A Method for Discovering Multiple Overlapping Clusterings , 2009 .
[26] Zoubin Ghahramani,et al. Variational Inference for Nonparametric Multiple Clustering , 2010 .
[27] A. Gelfand,et al. The Nested Dirichlet Process , 2008 .
[28] Michael I. Jordan. Hierarchical Models , Nested Models and Completely Random Measures , 2010 .
[29] Thomas L. Griffiths,et al. The nested chinese restaurant process and bayesian nonparametric inference of topic hierarchies , 2007, JACM.
[30] Ronenn Roubenoff,et al. Convergent Random Forest predictor: methodology for predicting drug response from genome-scale data applied to anti-TNF response. , 2009, Genomics.
[31] Katherine A. Heller,et al. Bayesian Sets , 2005, NIPS.
[32] Ammarin Thakkinstian,et al. How to use an article about genetic association: B: Are the results of the study valid? , 2009, JAMA.
[33] R. Tibshirani,et al. Sparse inverse covariance estimation with the lasso , 2007, 0708.3517.
[34] Michael I. Jordan,et al. Hierarchical Dirichlet Processes , 2006 .
[35] Joshua B. Tenenbaum,et al. AClass: A simple, online, parallelizable algorithm for probabilistic classification , 2007, AISTATS.
[36] M. Escobar,et al. Markov Chain Sampling Methods for Dirichlet Process Mixture Models , 2000 .
[37] John E. Wennberg,et al. Tracking the Care of Patients with Severe Chronic Illness: The Dartmouth Atlas of Health Care 2008 , 2008 .
[38] Radford M. Neal. Markov Chain Sampling Methods for Dirichlet Process Mixture Models , 2000 .
[39] Thomas L. Griffiths,et al. Hierarchical Topic Models and the Nested Chinese Restaurant Process , 2003, NIPS.
[40] L. Shapley,et al. Statistics, probability, and game theory : papers in honor of David Blackwell , 1999 .
[41] Sebastian Thrun,et al. Text Classification from Labeled and Unlabeled Documents using EM , 2000, Machine Learning.
[42] Richard S. Zemel,et al. Learning Parts-Based Representations of Data , 2006, J. Mach. Learn. Res..
[43] Nir Friedman,et al. Discovering Hidden Variables: A Structure-Based Approach , 2000, NIPS.
[44] J. Rosenthal,et al. Markov Chain Monte Carlo , 2018 .
[45] Elliott Fisher,et al. Health Care Spending , Quality , and Outcomes More Isn ’ t Always Better , 2009 .
[46] Joshua B. Tenenbaum,et al. A probabilistic model of cross-categorization , 2011, Cognition.
[47] Patrick Shafto,et al. Bayesian Hierarchical Cross-Clustering , 2011, AISTATS.
[48] Sayan Mukherjee,et al. Feature Selection for SVMs , 2000, NIPS.
[49] Y. Benjamini,et al. Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .
[50] P. Green,et al. Decomposable graphical Gaussian model determination , 1999 .
[51] D. Dunson,et al. Nonparametric Bayes Modeling of Multivariate Categorical Data , 2009, Journal of the American Statistical Association.
[52] Sylvia Richardson,et al. Markov Chain Monte Carlo in Practice , 1997 .
[53] Eric Jonas,et al. Scaling Nonparametric Bayesian Inference via Subsample-Annealing , 2014, AISTATS.
[54] J. Pitman. Some developments of the Blackwell-MacQueen urn scheme , 1996 .
[55] J. Tenenbaum,et al. Generalization, similarity, and Bayesian inference. , 2001, The Behavioral and brain sciences.
[56] D. Beer,et al. MicroRNA classifiers for predicting prognosis of squamous cell lung cancer. , 2009, Cancer research.
[57] Daniel M. Roy,et al. AClass : An online algorithm for generative classification , 2007 .
[58] J. Franklin,et al. The elements of statistical learning: data mining, inference and prediction , 2005 .
[59] Vikash K. Mansinghka,et al. Learning Cross-cutting Systems of Categories , 2006 .
[60] Kevin Murphy,et al. Bayes net toolbox for Matlab , 1999 .
[61] Joshua B. Tenenbaum,et al. Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs , 2013, NIPS.